Affine Space Research Articles

Characterizing an online, science-based affinity space using topic modelling, diversity indices, and social network analysis

Characterizing an online, science-based affinity space using topic modelling, diversity indices, and social network analysis

The primacy model and the structure of olfactory space.

Understanding sensory processing relies on the establishment of a consistent relationship between the stimulus space, its neural representation, and perceptual quality. In olfaction, the difficulty in establishing these links lies partly in the complexity of the underlying odor input space and perceptual responses. Based on the recently proposed primacy model for concentration invariant odor identity representation and a few assumptions, we have developed a theoretical framework for mapping the odor input space to the response properties of olfactory receptors. We analyze a geometrical structure containing odor representations in a multidimensional space of receptor affinities and describe its low-dimensional implementation, the primacy hull. We propose the implications of the primacy hull for the structure of feedforward connectivity in early olfactory networks. We test the predictions of our theory by comparing the existing receptor-ligand affinity and connectivity data obtained in the fruit fly olfactory system. We find that the Kenyon cells of the insect mushroom body integrate inputs from the high-affinity (primacy) sets of olfactory receptors in agreement with the primacy theory.

Enhancing ZnO/Si Heterojunction Solar Cells: A Combined Experimental And Simulation Approach

In this study, we explore the fabrication and optimization of ZnO/Si heterojunction solar cells to enhance their performance through precise control of electron affinity and bandgap properties. ZnO thin films were synthesized using thermal oxidation in a high-vacuum chamber, followed by annealing to improve crystallinity and electrical characteristics. The photovoltaic performance of the ZnO/Si heterojunction solar cells was systematically characterized, and Quantum ESPRESSO simulations were employed to refine the electronic properties of ZnO. Our results show significant improvements in open-circuit voltage, short-circuit current density, and overall conversion efficiency. The optimization of ZnO/Si heterojunction solar cells involves enhancing the electronic properties of ZnO thin films. Quantum ESPRESSO simulations were utilized to optimize the ZnO structure, calculate the band structure and density of states (DOS), and study the effects of Ga and Mg doping on the electronic properties of ZnO. The initial step in our study involved the structural optimization of ZnO to determine its lowest energy configuration. The optimization of the band offset engineering to improve the efficiency of n-ZnO/p-Si photovoltaic cells was found to be critical. Doping ZnO with Ga and Mg improved the band alignment with Si, reduced recombination losses, and enhanced charge carrier mobility. Our findings underscore the potential of optimized ZnO/Si heterojunction solar cells for high-efficiency solar energy conversion, demonstrating their viability as cost-effective and efficient solutions for renewable energy applications. This study highlights the importance of precise material engineering and simulation-driven optimization in developing advanced photovoltaic devices.

Identification of Difference Equations by Observations of Solutions with Perturbations from a Linear Manifold

Identification of Difference Equations by Observations of Solutions with Perturbations from a Linear Manifold

Affinity Uncertainty-Based Hard Negative Mining in Graph Contrastive Learning.

Hard negative mining has shown effective in enhancing self-supervised contrastive learning (CL) on diverse data types, including graph CL (GCL). The existing hardness-aware CL methods typically treat negative instances that are most similar to the anchor instance as hard negatives, which helps improve the CL performance, especially on image data. However, this approach often fails to identify the hard negatives but leads to many false negatives on graph data. This is mainly due to that the learned graph representations are not sufficiently discriminative due to oversmooth representations and/or non-independent and identically distributed (non-i.i.d.) issues in graph data. To tackle this problem, this article proposes a novel approach that builds a discriminative model on collective affinity information (i.e., two sets of pairwise affinities between the negative instances and the anchor instance) to mine hard negatives in GCL. In particular, the proposed approach evaluates how confident/uncertain the discriminative model is about the affinity of each negative instance to an anchor instance to determine its hardness weight relative to the anchor instance. This uncertainty information is then incorporated into the existing GCL loss functions via a weighting term to enhance their performance. The enhanced GCL is theoretically grounded that the resulting GCL loss is equivalent to a triplet loss with an adaptive margin being exponentially proportional to the learned uncertainty of each negative instance. Extensive experiments on ten graph datasets show that our approach does the following: 1) consistently enhances different state-of-the-art (SOTA) GCL methods in both graph and node classification tasks and 2) significantly improves their robustness against adversarial attacks. Code is available at https://github.com/mala-lab/AUGCL.

Recent Advances in Trifluoromethylation of Olefins, Aldehydes, and Ketones

: Due to the robust electrophilic properties of the trifluoromethyl group (-CF3), its incorporation into organic compounds can markedly alter their ester affinity, stability, bioavailability, and other properties. The trifluoromethylation reaction is currently experiencing rapid advancement, with an expanding array of substrates and the emergence of novel methodologies. Consequently, compounds containing the -CF3 moiety find extensive utility across diverse fields. This article aims to comprehensively review the latest advancements in trifluoromethylation reaction of olefins, aldehydes, and ketones, encompassing nucleophilic trifluoromethylation, electrophilic trifluoromethylation, and radical trifluoromethylation. The discussion includes an exploration of the types and broadening scope of applicable substrates. Furthermore, this article addresses the associated challenges and delineates prospective directions for future developments in trifluoromethyl reaction.

Linear sections of determinantal varieties

Denote Mmn(k) to be the set of all m n matrices over k, and PMmn(k) to be its affine space. Let Dm,n,r PMmn(k) be the subvariety consisting of the projective classes of all m n matrices with rank less than or equal to r. We study the minimal integer k > 0 such that for any linear subspace L of dimension k in PMmn(k), Dm,n,r L = . We get some partial results about this problem. Specially, when m = n = r + 1, we solve this problem for k = R, C and Q.

Self-healing and recyclable polyurethane-based solid-state polymer electrolyte via Diels-Alder dynamic network

Compared with liquid electrolytes, solid-state polymer electrolytes (SPEs) with better thermal, mechanical stability and processablilty are urgently required for the development of next-generation flexible energy storage devices. Herein, a series of polyurethane-based solid polymer electrolytes (PUBXSPE) with cross-linking structure were prepared by Diels-Alder reaction. The hydrogen bonding between the urea groups and dynamic Diels-Alder reaction endows the solid polymer electrolyte with excellent self-healing ability without external stimuli at room temperature. The PUBXSPE also displays good liquid affinity and superior recyclable properties, which provide a practical idea for the design of multifunctional polymer electrolytes. Although the cross-linking solid polymer electrolytes films display unsatisfied ionic conductivity about 10−6 S cm−1 at 60°C, the ionic conductivity value of the self-healing and recycled PUB1SPE were close to their pristine one. The wide working voltage window of PUBXSPE (>5.0 V) indicate that they can meet the requirements of most cathode materials. Moreover, the Li|PUB1SPE|LiFePO4 maintained a good coulombic efficiency (> 98.0 %) throughout all the cycle at 60°C, and the flexible cells can successfully light the blue diode under harsh conditions. This work provides new insights and concepts to design flexible, reliable, and safe polymer electrolytes for electronic devices at high-temperature.

A novel HER2 targeting nanoagent self-assembled from affibody-epothilone B conjugate for cancer therapy

Epothilone B (Epo B), a promising antitumor compound effective against various types of cancer cells in vitro. However, its poor selectivity for tumor cells and inadequate therapeutic windows significantly limit its potential clinical application. Affibody is a class of non-immunoglobulin affinity proteins with precise targeting capability to overexpressed molecular receptors on cancer cells, has been intensively investigated due to its exceptional affinity properties. In this study, we present a targeted nanoagent self-assembled from the precursor of an affibody conjugated with Epo B via a linker containing the thioketal (tk) group that is sensitive to reactive oxygen species (ROS). The core-shell structure of the ZHER2:342-Epo B Affibody-Drug Conjugate Nanoagent (Z-E ADCN), with the cytotoxin Epo B encapsulated within the ZHER2:342 affibody corona, leads to significantly reduced side effects on normal organs. Moreover, the abundant presence of ZHER2:342 on the surface effectively enhances the targeting capacity and tumor accumulation of the drug. Z-E ADCN can be internalized by cancer cells via HER2 receptor-mediated endocytosis followed by Epo B release in response to high levels of ROS, resulting in excellent anticancer efficacy in HER2-positive tumor models.

Exact hydrodynamic manifolds for the linear Boltzmann BGK equation I: spectral theory

We perform a complete spectral analysis of the linear three-dimensional Boltzmann BGK operator resulting in an explicit transcendental equation for the eigenvalues. Using the theory of finite-rank perturbations, we confirm the existence of a critical wave number kcrit\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$k_{\ extrm{crit}}$$\\end{document} which limits the number of hydrodynamic modes in the frequency space. This implies that there are only finitely many isolated eigenvalues above the essential spectrum at each wave number, thus showing the existence of a finite-dimensional, well-separated linear hydrodynamic manifold as a combination of invariant eigenspaces. The obtained results can serve as a benchmark for validating approximate theories of hydrodynamic closures and moment methods and provides the basis for the spectral closure operator.

Tuning the push-pull dyes: Construction of polarity insensitive probes for G4 DNA

We report here the design and synthesis of two new polarity-insensitive push-pull dyes TCP-SO3 and TCP-COOH and developed as fluorescent probes for G-quadruplex (G4) DNAs. The strategy involved in this study is to use the traditional D-π-A building block of carbazole-pyridinium (CP), while introducing of a diphenylimidazole group as a secondary donor as well as molecular rotor to form the D-D-π-A configuration, thus ascertaining the effect of the auxiliary group on the photophysics of the dyes. Additionally, N-sulfobutylpyridinium and N-(carboxyethyl) pyridinium bromide moieties are employed as electron-withdrawing anchoring groups, respectively, due to their hydrophilicity and electronic characters, thereby regulating the G4 DNA binding affinity and photophysical properties. It was found that the introduction of diphenylimidazole group to form the D-D-π-A configuration brought superior performance, in terms of polarity-insensitive property with a fluorescence-off state in various polarity solvents. Both dyes exhibited a clear-cut off-on sensing preference for G4 over non-G4 DNA structures, dye TCP-SO3 having a hydrophilic sulfonate group at electron-acceptor part displayed superior G4 DNA binding and selectivity compared to TCP-COOH with a carboxylic acid group. Detailed investigation on the relationship between the structure, photophysical properties, and G4 DNA sensing performance was described.

Ligand-Based Virtual Screening as a Path to New Chemotypes for Candidate PET Radioligands for Imaging Tauopathies.

Ligand-based virtual screening (LBVS) has rarely been tested as a method for discovering new structural scaffolds for PET radioligand development. This study used LBVS to discover potential chemotype leads for developing radioligands for PET imaging of tauopathies. ZINC12, a free database of over 12 million commercially available compounds, was searched to discover novel scaffolds based on similarities to four query compounds. Thirteen high-ranking hits were purchased and assayed for their ability to compete against three tritiated radioligands at their distinct binding sites in Alzheimer's disease brain tissue. Three hits were 2-substituted 6-methoxy naphthalenes. Synthetic elaboration of this new chemotype yielded three new ligands (25, 26, and 28) with high affinity for the [3H]6 (flortaucipur) neurofibrillary tangle binding site. Compound 28 showed remarkably high affinity (Ki, 7 nM) and other desirable properties for a candidate PET radioligand, including low topological polar surface area, moderate computed log D, and amenability for labeling with carbon-11. LBVS appears to be uniquely valuable for discovering new chemotypes for candidate PET radioligands.

Multilevel sources of strength and school-based racial discrimination: Competing factors associated with mental health among African American college students.

Despite increasing diversity on predominantly White college campuses, African American college students remain subject to racial discrimination, creating a complex array of mental health stressors. In this study, we adopted a strengths-based approach to mental health in this population and investigated (a) whether school-based discrimination contributes to negative mental health outcomes; (b) whether internal, interpersonal, and campus sources of strength contribute to positive mental health outcomes; and (c) whether internal sources of strength moderate the mental health effects of discrimination. Secondary analysis was performed on public data from African American college students (N = 1,444; Mage = 24.67, SDage = 7.87) who participated in the Healthy Minds Study between 2017 and 2020. Healthy Minds Study is a cross-sectional survey examining mental health factors in U.S. university student populations. School-based racial discrimination was negatively associated with flourishing and positively associated with depression. Flourishing was positively associated with all sources of strength, including academic persistence, religiosity, racial identity, race-based affinity space involvement, and campus climate for diversity. Depression was inversely associated with persistence, religiosity, and affinity space involvement. Except for persistence, internal sources of strength did not mitigate the negative effects of discrimination on mental health outcomes. Policies are needed that hold accountable campus members who perpetrate race-based aggressions, tangible support systems involving African American mentors and cultural affinity groups, and strengths-based audits of students seeking mental health care. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A Structure-based Data Set of Protein-peptide Affinities and its Nonredundant Benchmark: Potential Applications in Computational Peptidology.

Peptides play crucial roles in diverse cellular functions and participate in many biological processes by interacting with a variety of proteins, which have also been exploited as a promising class of therapeutic agents to target druggable proteins over the past decades. Understanding the intrinsic association between the structure and affinity of protein-peptide interactions (PpIs) should be considerably valuable for the computational peptidology area, such as guiding protein-peptide docking calculations, developing protein-peptide affinity scoring functions, and designing peptide ligands for specific protein receptors. We attempted to create a data source for relating PpI structure to affinity. By exhaustively surveying the whole protein data bank (PDB) database as well as the ontologically enriched literature information, we manually curated a structure- based data set of protein-peptide affinities, PpI[S/A]DS, which assembled over 350 PpI complex samples with both the experimentally measured structure and affinity data. The data set was further reduced to a nonredundant benchmark consisting of 102 culled samples, PpI[S/A]BM, which only selected those of structurally reliable, functionally diverse and evolutionarily nonhomologous. The collected structures were resolved at a high-resolution level with either Xray crystallography or solution NMR, while the deposited affinities were characterized by dissociation constant, i.e. Kd value, which is a direct biophysical measure of the intermolecular interaction strength between protein and peptide, ranging from subnanomolar to millimolar levels. The PpI samples in the set/benchmark were arbitrarily classified into α-helix, partial α-helix, β-sheet formed through binding, β-strand formed through selffolding, mixed, and other irregular ones, totally resulting in six classes according to the secondary structure of their peptide ligands. In addition, we also categorized these PpIs in terms of their biological function and binding behavior. The PpI[S/A]DS set and PpI[S/A]BM benchmark can be considered a valuable data source in the computational peptidology community, aiming to relate the affinity to structure for PpIs.

In silico analysis of potential inhibitors for breast cancer targeting 17beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD1) catalyses.

Breast cancer (BC) is still one of the major issues in world health, especially for women, which necessitates innovative therapeutic strategies. In this study, we investigated the efficacy of retinoic acid derivatives as inhibitors of 17beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD1), which plays a crucial role in the biosynthesis and metabolism of oestrogen and thereby influences the progression of BC and, the main objective of this investigation is to identify the possible drug candidate against BC through computational drug design approach including PASS prediction, molecular docking, ADMET profiling, molecular dynamics simulations (MD) and density functional theory (DFT) calculations. The result has reported that total eight derivatives with high binding affinity and promising pharmacokinetic properties among 115 derivatives. In particular, ligands 04 and 07 exhibited a higher binding affinity with values of -9.9 kcal/mol and -9.1 kcal/mol, respectively, than the standard drug epirubicin hydrochloride, which had a binding affinity of -8.2 kcal/mol. The stability of the ligand-protein complexes was further confirmed by MD simulations over a 100-ns trajectory, which included assessments of hydrogen bonds, root mean square deviation (RMSD), root mean square Fluctuation (RMSF), dynamic cross-correlation matric (DCCM) and principal component analysis. The study emphasizes the need for experimental validation to confirm the therapeutic utility of these compounds. This study enhances the computational search for new BC drugs and establishes a solid foundation for subsequent experimental and clinical research.

Microfluidic device: A versatile biosensor platform to multiplex aptamer-based detection of malaria biomarkers.

Plasmodium falciparum malaria remains a dominant infectious disease that affects Africa than the rest of the world, considering its associated cases and death rates. It's a febrile illness that produces several reliable biomarkers, for example, P. falciparum lactate dehydrogenase (PfLDH), P. falciparum Plasmodium glutamate dehydrogenase (PfGDH), and P. falciparum histidine-rich proteins (HRP-II) in blood circulatory system that can easily be employed as targets in rapid diagnostic tests (RDTs). In recent times, several DNA aptamers have been developed via SELEX technology to detect some specific malaria biomarkers (PfLDH, PvLDH, HRP-II, PfGDH) in a biosensor mode with good binding affinity properties to overcome the trend of cross-reactivity, limited sensitivity and stability problems that have been observed with immunodiagnostics. In this review, we summarized existing diagnostic methods and relevant biomarkers to suggest promising approaches to develop sensitive and species-specific multiplexed diagnostic devices enabling effective detection of malaria in complex biological matrices and surveillance in the endemic region.

Calculated Aqueous Reduction Potentials of Neutral and Anionic Halogen Diatomic Molecules.

The free energy of hydration, aqueous, and gas phase electron affinity and aqueous reduction potentials of F2, Cl2, Br2, I2, ClF, BrF, IF, BrCl, ICl, IBr, and their corresponding anions were calculated using an electronic structure approach previously developed for these properties for X• and XO•, where X is a halogen which yielded excellent results. The gas phase electron affinities were calculated at the Feller-Peterson-Dixon level based on complete basis set extrapolation of CCSD(T) results with additional corrections. The agreement with the available experimental data is excellent, and the calculations provide a complete set of reliable electron affinities for these diatomic halogens. The hybrid solvation approach uses single point implicit solvation calculations on gas phase optimized clusters with explicit solvent molecules. The gas phase energy calculations were performed using MP2 and CCSD(T)-F12b for tetramer clusters (four explicit waters) and MP2 for octamer clusters (eight explicit waters). The final redox potentials were obtained at the MP2/aug-cc-pVTZ (aT) with a self-consistent reaction field (SMD) level using the octamer clusters. The aqueous reduction potentials of the neutral diatomic halogens are predicted within 0.06 V of the experiment for diatomic neutrals. The same agreement of 0.06 V is predicted for the redox potential resulting from dissociation electron attachment of the diatomic halogen anions. The current work extends reduction potentials for multiple redox couples for which no experimental data is available, for example, those containing iodine and the interhalogen anions. F2•- is predicted to dissociate for its lowest energy structure in both the tetramer and octamer clusters to form solvated F-, HF, and OH•.

A single-domain antibody library based on a stability-engineered human VH3 scaffold

Using conventional immunoglobulin G (IgG) molecules as therapeutic agents presents several well-known disadvantages owing to their large size and structural complexity, negatively impacting development and production efficiency. Single-domain antibodies (sdAbs) are the smallest functional antibody format (~ 15 kDa) and represent a viable alternative to IgG in many applications. However, unlike natural single-domain antibodies, such as camelid VHH, the variable domains of conventional antibodies show poor physicochemical properties when expressed as sdAbs. This report identified stable sdAb variants of human VH3-23 from a framework region 2-randomized human VH library by phage display selection under thermal challenge. Synthetic complementarity determining region diversity was introduced to one of the selected variants with high thermal stability, expression level, and monomeric content to construct a human VH sdAb library. The library was validated by panning against a panel of antigens, and target-specific binders were identified and characterized for their affinity and biophysical properties. The results of this study suggest that a synthetic sdAb library based on a stability-engineered human VH scaffold could be a facile source of high-quality sdAb for many practical applications.

Three-dimensional quasi-umbilical locally strongly convex homogeneous affine hypersurfaces

The study of strongly convex, locally homogeneous hypersurfaces in the affine space ℝn+1 has a rich history. In dimension 2, these hypersurfaces were first examined in Guggenheimer's 1977 book “Differential Geometry” [4], and the classification was completed by Nomizu and Sasaki in their 1991 paper “A new model of unimodular-affinely homogeneous surfaces” [6]. Apart from the work of Magid and Vrancken in their 1995 paper [5] and Ooguri’s 2013 paper [9], most studies have focused on locally strongly convex affine hypersurfaces. These are characterized by an induced affine metric that is positive definite, and have been extensively studied in Sasaki’s 1980 paper “Hyperbolic affine hyperspheres” [10]. When the hypersurface is an affine sphere, where the shape operator has all eigenvalues equal to zero, Dillen and Vrancken provided a complete classification in a series of papers. In dimension 3, their 1993 paper “The classification of 3-dimensional locally strongly convex homogeneous affine hypersurfaces” [3] offers a comprehensive classification for any dimensions of eigenvalues of the shape operator. In dimension 4, the quasi-umbilical case was explored by Dillen and Vrancken in their 1994 paper “Quasi-umbilical, locally strongly convex homogeneous affine hypersurfaces” [2]. The case where the affine shape operator has two distinct eigenvalues, each with a multiplicity of two, was investigated by Chikh-Salah and Vrancken in their 2017 paper “Four-dimensional locally strongly convex homogeneous affine hypersurfaces” [1]. In this paper, we provide a different proof of the final theorem in Dillen and Vrancken’s [3], utilizing Mathematica software to calculate all Christoffel symbol functions.

Copper Overload Increased Rat Striatal Levels of Both Dopamine and Its Main Metabolite Homovanillic Acid in Extracellular Fluid.

Copper is a trace element whose electronic configuration provides it with essential structural and catalytic functions. However, in excess, both its high protein affinity and redox-catalyzing properties can lead to hazardous consequences. In addition to promoting oxidative stress, copper is gaining interest for its effects on neurotransmission through modulation of GABAergic and glutamatergic receptors and interaction with the dopamine reuptake transporter. The aim of the present study was to investigate the effects of copper overexposure on the levels of dopamine, noradrenaline, and serotonin, or their main metabolites in rat's striatum extracellular fluid. Copper was injected intraperitoneally using our previously developed model, which ensured striatal overconcentration (2 mg CuCl2/kg for 30 days). Subsequently, extracellular fluid was collected by microdialysis on days 0, 15, and 30. Dopamine (DA), 3,4-dihydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA), 5-hydroxyindoleacetic acid (5-HIAA), and noradrenaline (NA) levels were then determined by HPLC coupled with electrochemical detection. We observed a significant increase in the basal levels of DA and HVA after 15 days of treatment (310% and 351%), which was maintained after 30 days (358% and 402%), with no significant changes in the concentrations of 5-HIAA, DOPAC, and NA. Copper overload led to a marked increase in synaptic DA concentration, which could contribute to the psychoneurological alterations and the increased oxidative toxicity observed in Wilson's disease and other copper dysregulation states.