Miracle-dz/UniFAR-FTUs huggingface dataset:
Glucokinase activators as new type 2 diabetes therapeutic agents

Background: Small molecule glucokinase activators (GKAs) represent a new strategy to treat type 2 diabetes. Glucokinase (GK) primarily exerts its effect through modulatory actions in the pancreatic β-cells and the liver. It couples insulin secretion in the pancreas with plasma glucose concentration, and improves glucose utilization in the liver, thus affecting two key aspects of glucose homeostasis. Objective and method: To review currently disclosed GKA structures and to classify them based on the key structural features. For this purpose, the data from patent disclosures and publications are used. Also, published in vitro findings on related lead GKAs are used to compare their effect on GK kinetics. Results and conclusion: The most common GKA pharmacophore consists of a center, which can be a carbon or an aromatic ring, and three attachments. Two of these are hydrophobic groups, with at least one of them being an aromatic ring. The third attachment, without exception, consists of an H-bond donor–acceptor pair in the form of a heterocyclic amine, or an N-acyl urea. These structurally diverse GKAs show important differences in their effects on the kinetic properties of GK.
A comparative investigation on linear inversion schemes in fluorescence lifetime tomography

Fluorescence lifetime tomography (FLT) is an emerging imaging modality that seeks for recovering distributions of the fluorescent yield and lifetime inside in vivo tissues. This technique, mainly based on time-domain instrumentation, has found promising applications in small-animal imaging for studying tumor pathology and for drug development. As one of the model-based imaging methods, FLT can be finalized with inverting an underdetermined, ill-posed linear system with regard to both the parameters, for which several methods has been adopted. This paper concisely revises the main facts of three commonly-used linear inversions: algebraic reconstruction technique, truncated singular value decomposition and conjugate gradient descent, and presents a comparative investigation on these methods in terms of the image quality and noise robustness.
Involvement of γ-Aminobutyric Acid (GABA) B Receptors in the Hypotensive Effect of Systemically Administered GABA in Spontaneously Hypertensive Rats

We investigated the effects of intraduodenally (i.d.) administered γ-aminobutyric acid (GABA) on blood pressure (BP) in anesthetized spontaneously hypertensive rats (SHR) and the mechanism underlying this effect, especially the type of GABA receptor involved in the depressive effect of this amino acid. GABA (0.3 to 300 mg/kg, i.d.) caused a dose-related decrease in the BP of 9.20 ± 3.96 to 35.0 ± 5.34 mmHg (mean ± S.E.M.) that lasted for 30 to 50 min. The minimum effective i.d. dose of GABA was 0.3 to 1.0 mg/kg. Results pertaining to the mechanism underlying the GABA-induced effects on BP were as follows: a) GABA did not alter the BP-related effects of exogenous noradrenaline and acetylcholine; b) pretreatment with hexamethonium decreased the GABA-induced fall in BP, and GABA tended to reduce the pressor response associated with injection of dimethyl phenylpiperazinium; and c) pretreatment with 2-hydroxysaclofen markedly reduced the GABA-induced drop in BP, whereas pretreatment with bicuculline did not. In conclusion, in SHR, low-dose (0.3 to 1.0 mg/kg, i.d.) GABA had a hypotensive effect, which may result from attenuation of sympathetic transmission through the activation of GABAB receptors at presynaptic or ganglionic sites.
Revealing the Relevant Spatiotemporal Scale Underlying Whole-Brain Dynamics

The brain rapidly processes and adapts to new information by dynamically transitioning between whole-brain functional networks. In this whole-brain modeling study we investigate the relevance of spatiotemporal scale in whole-brain functional networks. This is achieved through estimating brain parcellations at different spatial scales (100–900 regions) and time series at different temporal scales (from milliseconds to seconds) generated by a whole-brain model fitted to fMRI data. We quantify the richness of the dynamic repertoire at each spatiotemporal scale by computing the entropy of transitions between whole-brain functional networks. The results show that the optimal relevant spatial scale is around 300 regions and a temporal scale of around 150 ms. Overall, this study provides much needed evidence for the relevant spatiotemporal scales and recommendations for analyses of brain dynamics.
Extraction of Uranyl Ion Using 2-Thenoyltrifluoro Acetone (HTTA) in Room Temperature Ionic Liquids

The extraction of UO22+ ion was studied using six different solvent systems containing 2-thenoyltrifluoroacetone (HTTA) in room temperature ionic liquids such as [Cnmim][X] (where, n = 4, 6, or 8 and X− = PF6− or NTf2−) from low to moderate pH solutions for the first time. The extraction kinetics studies indicated rather slow attainment of equilibrium which in some cases improved if the solutions were pre-equilibrated with the aqueous phase prior to the actual experiments. The DU values were found to increase with increasing pH and leading to a plateau like profile at higher pH values. The D values were quite high as compared to that obtained with molecular diluents. The nature of the extracted species was ascertained by slope analysis method which suggested species of the type: UO2(TTA)+IL, UO2(TTA)2,IL, and UO2(TTA)2(HTTA)IL in different ionic liquid based solvents. Temperature variation studies on UO22+ ion extraction were also carried out and the thermodynamic parameters were calculated which indicated high endothermicity of the reactions with large positive entropy values.
Does there exist an intrinsic relationship between the flexibility and self-assembly of pepfactants?

Short peptide surfactants (pepfactants) bearing the amphiphilic molecular architecture of hydrophobic and hydrophilic moieties are attractive for a wide range of biological and medical applications. Understanding of structural basis and molecular mechanism underlying the self-assembling behaviour of pepfactants is fundamentally important for rationally designing surfactant-like peptides to function as diverse biomaterials. To date, however, the relationship between the physicochemical properties and self-assembly of pepfactants still remains largely unexplored. In this study, we attempt to elucidate the role of structural flexibility and dynamics in peptide self-assembly. Two fast and reliable quantitative structure–property relationship predictors are carefully developed with the sophisticated genetic algorithm/partial least squares method; the predictors are then applied to estimate molecular flexibility and self-assembling ability for 10,000 randomly generated surfactant-like peptides. As a result, a significant negative correlation between the flexibility and self-assembly is observed, which can be fitted fairly well using an exponential curve. Furthermore, atomistic molecular dynamics simulations also reveal a noticeable difference of flexibility profile between strong and weak self-assembling peptides. All these come together to suggest that the self-assembling behaviour of pepfactants is highly dependent on their structural flexibility.
The evaluation of dupilumab treatment response in atopic dermatitis patients

OBJECTIVE: This study aims to demonstrate real-life effectiveness of dupilumab treatment in moderate-to-severe atopic dermatitis patients. METHODS: The 14 patients diagnosed with moderate-to-severe atopic dermatitis were included in this study. All of the patients started dupilumab treatment in our faculty between October 2019 and October 2020. The patients were evaluated at the beginning of the treatment and after 12 weeks of treatments. The baseline scoring atopic dermatitis (SCORAD) scores, the total immunoglobulin E (IgE) levels, and the visual analog scale (VAS) of 0–10 points for itch intensity compared with the post-treatment scores. RESULTS: The SCORAD scores, the serum total IgE levels, and the VAS itch scores of the patients receiving dupilumab treatment dropped significantly following 12 weeks of dupilumab treatment. No significant correlation was demonstrated between the initial SCORAD scores and the serum total IgE values. Besides, no correlation was shown to exist in the reduction of the SCORAD and the serum total IgE values after dupilumab treatment. CONCLUSION: Dupilumab treatment showed significant improvement in disease severity with remarkable reduction in serum total IgE levels.
DIP: Natural History Model for Major Depression with Incidence and Prevalence

Background. Major depression is a treatable disease, and untreated depression can lead to serious health complications. Therefore, prevention, early identification, and treatment efforts are essential. Natural history models can be utilized to make informed decisions about interventions and treatments of major depression. Methods. We propose a natural history model of major depression. We use steady-state analysis to study the discrete-time Markov chain model. For this purpose, we solved differential equations and tested the parameter and transition probabilities empirically. Results. We showed that bias in parameters might collectively cause a significant mismatch in a model. If incidence is correct, then lifetime prevalence is 33.2% for females and 20.5% for males, which is higher than reported values. If prevalence is correct, then incidence is . 0008 for females and . 00065 for males, which is lower than reported values. The model can achieve feasibility if incidence is at low levels and recall bias of the lifetime prevalence is quantified to be 31.9% for females and 16.3% for males. Limitations. Model is limited to major depression, and patients who have other types of depression are assumed healthy. We assume that transition probabilities (except incidence rates) are correct. Conclusion. We constructed a preliminary model for the natural history of major depression. We determine the lifetime prevalence are underestimated. We conclude that the average incidence rates may be underestimated for males. Our findings mathematically prove the arguments around the potential discordance between reported incidence and lifetime prevalence rates.
Dynamic versus Continuous Interventions: Optimizing Lockdown Policies for COVID-19

In the context of the ongoing COVID-19 pandemic, while millions of people await the administration of a vaccine, social distancing remains the leading approach towards the effect commonly known as "flattening the curve" of infections. Over the last year, governmental administrations throughout the globe have implemented various lockdown policies in hopes of slowing down the transmission of the disease. However, the current lack of consensus on when and how these policies should be implemented reflects the need for further studies regarding these questions. In this paper, we tackle the issue of lockdown policy management, in particular in terms of lockdown placement (how often, when, and how long these periods should be), in order to minimize the peak of infections in a specific population. We introduce a novel combination of classic mathematical disease modelling using the equation-based SEIR model, and Evolutionary Strategies (ES) for optimizing the peak of infections. The method is evaluated using data collected in different countries, and a particular focus is placed on the study of the effect of specific model parameters on lockdown optimization, such as the transmission rate ($beta$), of which 4 alternative modelling functions have been proposed and analyzed. Our results indicate that this transmission rate parameter significantly influences the resulting optimal strategies. In particular, the presence of a gradual decay of the rate of transmission during lockdown leads to longer, more sparsely placed confinement periods while an abrupt, instantaneous drop in the amount of contacts per person favors shorter but more frequent lockdowns. Although these results are limited by the scope of action provided by the simplicity of the SEIR model, they suggest that the influence of the evolution of the rate of transmission along the disease should be assessed in further studies with alternative optimization strategies (agent-based) and models (SEIRSHUD).
A class of two-d imens iona l sys tems

We consider systems of the hydrodynamic type in the sense of Dubrovin and Novikov (see [1, 2]). In particular, we consider the recursion operators introduced and discuss(,d in [3, 4]. Sheftel showed [5] that the general recursion operator associated with a general two-dimensional diagonal hydrodynamic system contains two arbitrary functions of a single variable that satisfy a differential constraint. However, when the hydrodynamic system belongs to the class considered in this paper, these arbi t rary functions take the specific form of one of three monomials, and there are therefore only three independent reeursion operators for a given system. The class we consider is fairly general and contains all examples known to us. The systems we consider are associated with a generalized Euler-Poisson-Darboux (EPD) / /nea r wave equat ion in the sense that for each such wave equation, we construct a family of commuting hydrodynamic systems and the corresponding triple of reeursion operators. Specific systems correspond to particular solutions of this wave equation. It is easy to construct ladder operators of these wave equations with which it is possible to generate hierarchies of connected solutions. The corresponding hydrodynamic systems are then connected through Teshukov-type recursion operators. These can then be used to generate "higher symmetries" by acting with them upon some simple symmetries that are not of the hydrodynamic type. Most of this paper is concerned with two-dimensional systems for simplicity of exposition, but our formulas are easily extended to higher dimensions (see See. 5).
Linear and Nonlinear Plasma Processes in Ionospheric HF

Featured observations of high frequency (HF) heating experiments are first introduced; the uniqueness of each observation is presented; the likely cause and physical process of each observed phenomenon instigated by the HF heating are discussed. A special point in the observations, revealed through the ionograms, is the competition between the Langmuir parametric instability and upper hybrid parametric instability excited in the heating experiments and the impact of the natural cusp at foE (the peak plasma frequency of the ionospheric E region) on the competition. The ionograms also infer the generation of Langmuir and upper hybrid cavitons. Ray tracing theory is formulated. With and without the appearance of large‐scale field‐aligned density irregularities in the background ionosphere, ray trajectories of the ordinary mode (O‐mode) and extraordinary mode (X‐mode) sounding pulses are calculated numerically. The results explain the artificial Spread‐F recorded by the digisondes in the heating experiments. Parametric instabilities, which are the directly relevant processes to achieve effective heating of the ionospheric F region, are formulated and analyzed. The threshold fields and growth rates of Langmuir and upper hybrid parametric instabilities are derived as the theoretical basis of many radar observations and electron‐ plasma wave interactions. Harmonic cyclotron resonance interaction processes between electrons and upper hybrid waves are introduced. Formulation and analysis are presented. The numerical results show that ultra‐energetic electrons are generated. These electrons enhance airglow at 777.4 nm as well as cause ionization. Physical processes leading to the generation of artificial ionization layers are discussed. The nonlinear Schrodinger equation governing the nonlinear evolution of Langmuir waves and upper hybrid waves are derived and solved. The nonlinear periodic and solitary solutions of the equations are obtained. The localized Langmuir and upper hybrid waves generated by the HF heater form cavitons near the HF reflection layer and near the upper hybrid resonance layer, which induce bumps in the virtual height spread of the ionogram trace similar to that induced by the density cusp at E‐F1 transition layer; the down‐going Langmuir waves and upper hybrid waves evolve into nonlinear periodic waves propagating along the magnetic field, which backscatter incoherently the sounding pulses to cause downward virtual height spread.
Variables affecting the thermal yellowing of TCF-bleached birch kraft pulps

The purpose of this investigation was to identify the most important variables influencing the thermal yellowing of TCF-bleached kraft pulps. The variables studied were: hexenuronic acid content, dry content, temperature, time, pH, and iron content. All these variables influence the process of colour reversion. It was shown that there is a strong relationship between hexenuronic acid content and the magnitude of the colour reversion. Of the conditions investigated, long time (6 days), high temperature (80 degreesC), slightly acidic conditions (pH 4.5) and a moist environment (92% dry content) caused the greatest brightness reversion. At 99% dry content the discoloration was insignificant. Impregnation of handsheets has shown that ferrous ions are more detrimental than ferric ions to the colour formation. It is suggested that the hydrolysis of hexenuronic acid into the known acidic degradation products, 2-furancarboxylic acid and 5-formyl-2-furancarboxylic acid can not be the rate limiting reaction in the colour formation. It is also suggested that new aromatic structures are formed during the thermal yellowing process. Finally it was shown that the discoloration can be partly washed away with water.
Understanding Concerns, Sentiments, and Disparities Among Population Groups During the COVID-19 Pandemic Via Twitter Data Mining: Large-scale Cross-sectional Study

Background Since the beginning of the COVID-19 pandemic in late 2019, its far-reaching impacts have been witnessed globally across all aspects of human life, such as health, economy, politics, and education. Such widely penetrating impacts cast significant and profound burdens on all population groups, incurring varied concerns and sentiments among them. Objective This study aims to identify the concerns, sentiments, and disparities of various population groups during the COVID-19 pandemic through a cross-sectional study conducted via large-scale Twitter data mining infoveillance. Methods This study consisted of three steps: first, tweets posted during the pandemic were collected and preprocessed on a large scale; second, the key population attributes, concerns, sentiments, and emotions were extracted via a collection of natural language processing procedures; third, multiple analyses were conducted to reveal concerns, sentiments, and disparities among population groups during the pandemic. Overall, this study implemented a quick, effective, and economical approach for analyzing population-level disparities during a public health event. The source code developed in this study was released for free public use at GitHub. Results A total of 1,015,655 original English tweets posted from August 7 to 12, 2020, were acquired and analyzed to obtain the following results. Organizations were significantly more concerned about COVID-19 (odds ratio [OR] 3.48, 95% CI 3.39-3.58) and expressed more fear and depression emotions than individuals. Females were less concerned about COVID-19 (OR 0.73, 95% CI 0.71-0.75) and expressed less fear and depression emotions than males. Among all age groups (ie, ≤18, 19-29, 30-39, and ≥40 years of age), the attention ORs of COVID-19 fear and depression increased significantly with age. It is worth noting that not all females paid less attention to COVID-19 than males. In the age group of 40 years or older, females were more concerned than males, especially regarding the economic and education topics. In addition, males 40 years or older and 18 years or younger were the least positive. Lastly, in all sentiment analyses, the sentiment polarities regarding political topics were always the lowest among the five topics of concern across all population groups. Conclusions Through large-scale Twitter data mining, this study revealed that meaningful differences regarding concerns and sentiments about COVID-19-related topics existed among population groups during the study period. Therefore, specialized and varied attention and support are needed for different population groups. In addition, the efficient analysis method implemented by our publicly released code can be utilized to dynamically track the evolution of each population group during the pandemic or any other major event for better informed public health research and interventions.
Microscopic models for quantum mechanical calculations of chemical processes in solutions: LD/AMPAC and SCAAS/AMPAC calculations of solvation energies

Our previously developed approaches for integrating quantum mechanical molecular orbital methods with microscopic solvent models are refined and examined. These approaches consider the nonlinear solute–solvent coupling in a self‐consistent way by incorporating the potential from the solvent dipoles in the solute Hamiltonian, while considering the polarization of the solvent by the potential from the solute charges. The solvent models used include the simplified Langevin Dipoles (LD) model and the much more expensive surface constrained All Atom Solvent (SCAAS) model, which is combined with a free energy pertubation (FEP) approach. Both methods are effectively integrated with the quantum mechanical AMPAC package and can be easily combined with other quantum mechanical programs. The advantages of the present approaches and their earlier versions over macroscopic reaction field models and supermolecular approaches are considered. A LD/MNDO study of solvated organic ions demonstrates that this model can yield reliable solvation energies, provided the quantum mechanical charges are scaled to have similar magnitudes to those obtained by high level ab initio methods. The incorporation of a field‐dependent hydrophobic term in the LD free energy makes the present approach capable of evaluating the free energy of transfer of polar molecules from non polar solvents to aqueous solutions. The reliability of the LD approach is examined not only by evaluating a rather standard set of solvation energies of organic ions and polar molecules, but also by considering the stringent test case of sterically hindered hydrophobic ions. In this case, we compare the LD/MNDO solvation energies to the more rigorous FEP/SCAAS/MNDO solvation energies. Both methods are found to give similar results even in this challenging test case. The FEP/SCAAS/AMPAC method is incorporated into the current version of the program ENZYMIX. This option allows one to study chemical reactions in enzymes and in solutions using the MNDO and AM1 approximations. A special procedure that uses the EVB method as a reference potential for SCF MO calculations should help in improving the reliability of such studies.
Accurate ab initio total atomization energies of the Cn clusters (n=2–10)

The total atomization energies of the carbon clusters Cn (n=2–10) have been calculated ab initio using augmented coupled‐cluster methods and basis sets of spdf and spdfg quality. The values agree to within experimental uncertainty with recent Knudsen effusion measurements for Cn (n=2–7), but suggest actual values on the high side of their experimental range. For the odd‐numbered clusters, an additivity approximation holds very well, and extrapolated ∑D0 values are proposed for C11, C13, C15, C17, and C19.