Miracle-dz/UniFAR-FTUs huggingface dataset:
Advances in the development and application of computational methodologies for structural modeling of G-protein-coupled receptors

Background: Despite the large amount of experimental data accumulated in the past decade on G-protein-coupled receptor (GPCR) structure and function, understanding of the molecular mechanisms underlying GPCR signaling is still far from being complete, thus impairing the design of effective and selective pharmaceuticals. Objective: Understanding of GPCR function has been challenged even further by more recent experimental evidence that several of these receptors are organized in the cell membrane as homo- or hetero-oligomers, and that they may exhibit unique pharmacological properties. Given the complexity of these new signaling systems, researchers' efforts are turning increasingly to molecular modeling, bioinformatics, and computational simulations for mechanistic insights of GPCR functional plasticity. Methods: We review here the current advancements in the development and application of computational approaches to improve prediction of GPCR structure and dynamics, thus enhancing current understanding of GPCR signaling. Results/conclusions: Models resulting from the use of these computational approaches further supported by experiments are expected to help explain the complex allosterism that propagates through GPCR complexes, ultimately aiming at successful structure-based rational drug design.
Ranking docked models of protein-protein complexes using predicted partner-specific protein-protein interfaces: a preliminary study

Computational protein-protein docking is a valuable tool for determining the conformation of complexes formed by interacting proteins. Selecting near-native conformations from the large number of possible models generated by docking software presents a significant challenge in practice. We introduce a novel method for ranking docked conformations based on the degree of overlap between the interface residues of a docked conformation formed by a pair of proteins with the set of predicted interface residues between them. Our approach relies on a method, called PS-HomPPI, for reliably predicting proteinprotein interface residues by taking into account information derived from both interacting proteins. PS-HomPPI infers the residues of a query protein that are likely to interact with a partner protein based on known interface residues of the homo-interologs of the query-partner protein pair, i.e., pairs of interacting proteins that are homologous to the query protein and partner protein. Our results on Docking Benchmark 3.0 show that the quality of the ranking of docked conformations using our method is consistently superior to that produced using ClusPro cluster-size-based and energy-based criteria for 61 out of the 64 docking complexes for which PS-HomPPI produces interface predictions. An implementation of our method for ranking docked models is freely available at: http://einstein.cs. iastate.edu/DockRank/.
Unveiling a Shield of Hope: A Novel Multiepitope-Based Immunogen for Cross-Serotype Cellular Defense against Dengue Virus

Dengue virus (DENV) infection continues to be a public health challenge, lacking a specific cure. Vaccination remains the primary strategy against dengue; however, existing live-attenuated vaccines display variable efficacy across four serotypes, influenced by host serostatus and age, and predominantly inducing humoral responses. To address this limitation, this study investigates a multiepitope-based immunogen designed to induce robust cellular immunity across all DENV serotypes. The chimeric immunogen integrates H-2d specific MHC-I binding T-cell epitopes derived from conserved domains within the DENV envelope protein. Immuno-informatics analyses supported its stability, non-allergenic nature, and strong MHC-I binding affinity as an antigen. To assess the immunogenicity of the multiepitope, it was expressed in murine bone-marrow-derived dendritic cells (BMDCs) that were used to prime mice. In this experimental model, simultaneous exposure to T-cell epitopes from all four DENV serotypes initiated distinct IFNγ-CD8 T-cell responses for different serotypes. These results supported the potential of the multiepitope construct as a vaccine candidate. While the optimization of the immunogen design remains a continuous pursuit, this proof-of-concept study provides a starting point for evaluating its protective efficacy against dengue infection in vivo. Moreover, our results support the development of a multiepitope vaccine that could trigger a pan-serotype anti-dengue CD8 response.
Evidence that Tobacco Smoking Increases the Density of (−)‐[3H]Nicotine Binding Sites in Human Brain

Abstract: In a postmortem study of nicotinic receptors in human brain, cigarette smoking was found to be associated with increased (−)‐[3H]nicotine binding to membranes prepared from gyrus rectus (Brodmann area 11) (p < 0.001), hippocampal neocortex (Brodmann area 27), cerebellar cortex (p < 0.01), hippocampal formation (Ammon's horn + subiculum), and the median raphe nuclei of the midbrain (p < 0.05) but not the medulla oblongata. Analysis of the binding data suggested that the increased binding reflected an increase in the density of the receptors rather than a change in their affinity for (−)‐nicotine. The effects of smoking were not influenced significantly by either the sex or age of the subject. It is concluded that smoking evokes an increase in high‐affinity nicotine binding similar to that observed previously in animals treated chronically with nicotine and that the effect of smoking on these sites is probably caused by the nicotine present in the tobacco smoke.
Epitope Mapping of Japanese Encephalitis Virus Neutralizing Antibodies by Native Mass Spectrometry and Hydrogen/Deuterium Exchange

Japanese encephalitis virus (JEV) remains a global public health concern due to its epidemiological distribution and the existence of multiple strains. Neutralizing antibodies against this infection have shown efficacy in in vivo studies. Thus, elucidation of the epitopes of neutralizing antibodies can aid in the design and development of effective vaccines against different strains of JEV. Here, we describe a combination of native mass spectrometry (native-MS) and hydrogen/deuterium exchange mass spectrometry (HDX-MS) to complete screening of eight mouse monoclonal antibodies (MAbs) against JEV E-DIII to identify epitope regions. Native-MS was used as a first pass to identify the antibodies that formed a complex with the target antigen, and it revealed that seven of the eight monoclonal antibodies underwent binding. Native mass spectra of a MAb (JEV-27) known to be non-binding showed broad native-MS peaks and poor signal, suggesting the protein is a mixture or that there are impurities in the sample. We followed native-MS with HDX-MS to locate the binding sites for several of the complex-forming antibodies. This combination of two mass spectrometry-based approaches should be generally applicable and particularly suitable for screening of antigen–antibody and other protein–protein interactions when other traditional approaches give unclear results or are difficult, unavailable, or need to be validated.
Reducing Risk with Clinical Decision Support

Summary Objective: Identify clinical opportunities to intervene to prevent a malpractice event and determine the proportion of malpractice claims potentially preventable by clinical decision support (CDS). Materials and Methods: Cross-sectional review of closed malpractice claims over seven years from one malpractice insurance company and seven hospitals in the Boston area. For each event, clinical opportunities to intervene to avert the malpractice event and the presence or absence of CDS that might have a role in preventing the event, were assigned by a panel of expert raters. Compensation paid out to resolve a claim (indemnity), was associated with each CDS type. Results: Of the 477 closed malpractice cases, 359 (75.3%) were categorized as substantiated and 195 (54%) had at least one opportunity to intervene. Common opportunities to intervene related to performance of procedure, diagnosis, and fall prevention. We identified at least one CDS type for 63% of substantiated claims. The 41 CDS types identified included clinically significant test result alerting, diagnostic decision support and electronic tracking of instruments. Cases with at least one associated intervention accounted for $40.3 million (58.9%) of indemnity. Discussion: CDS systems and other forms of health information technology (HIT) are expected to improve quality of care, but their potential to mitigate risk had not previously been quantified. Our results suggest that, in addition to their known benefits for quality and safety, CDS systems within HIT have a potential role in decreasing malpractice payments. Conclusion: More than half of malpractice events and over $40 million of indemnity were potentially preventable with CDS. Citation: G. Zuccotti G, Maloney FL, Feblowitz J, Samal L, Sato L, Wright A. Reducing risk with clinical decision support: A study of closed malpractice claims. Appl Clin Inf 2014; 5: 746–756 http://dx.doi. org/10.4338/ACI-2014-02-RA-0018
Psychometric Validation of the Persian Version of Multidimensional Health Locus of Control Scale (MHLC-C) for Menopausal Women

Background. The Health Locus of Control (HLC) serves as a mediator between an individual’s behaviors and health status, influenced by various cultural, environmental, and situational factors. Its measurement reflects health beliefs and attitudes, ultimately leading to healthy behaviors. Menopause is a significant phenomenon in women’s lives, often resulting in a wide range of symptoms and health issues. Therefore, the perception of HLC plays a crucial role in promoting healthy behaviors and managing menopausal symptoms. This study aimed to assess the validity and reliability of the Persian version of the short form Multidimensional Health Locus of Control Scale (MHLC) in Iranian menopausal women and explore its interrelationships. Methods. A cross-sectional study was conducted with 271 menopausal women from September to November 2023. Psychometric properties such as construct validity (confirmed through confirmatory factor analysis), convergent validity (evaluated using average variance extracted), and internal consistency (assessed by Cronbach’s alpha, composite reliability and rho_A factor) were examined. Discriminant validity was determined using the Fornell–Larcker criterion. Reliability was further established through Cronbach’s alpha and McDonald’s Omega coefficients. The predictive relevance of the model and associations between constructs were analyzed using various statistical measures. Data analysis was conducted using SPSS v.27 and Smart PLS 3.0 software. Limitations of this study include that it was conducted in urban health centers, only women with at least primary education were included, and reliance on self-reported data. Results. The initial stage of construct validity involved the Kolmogorov–Smirnov test, with confirmatory factor analysis demonstrating a good model fit. Significant correlations were found between internal health control and factors related to doctors and other people, indicating that internal health control directly influences these factors in managing menopausal symptoms and health problems. Cronbach’s alpha and McDonald’s Omega coefficients for the 13-item MHLC-C scale were satisfactory (0.81 and 0.72, respectively). Conclusions. The Persian version of the 13-item MHLC-C has been validated as a reliable tool for assessing the health locus of control in Iranian menopausal women. Internal health control was found to significantly impact perceptions related to doctors and other people, highlighting its importance in managing menopausal symptoms effectively.
Crystallization of Ethylene Plant Hormone Receptor—Screening for Structure

The plant hormone ethylene is a key regulator of plant growth, development, and stress adaptation. Many ethylene-related responses, such as abscission, seed germination, or ripening, are of great importance to global agriculture. Ethylene perception and response are mediated by a family of integral membrane receptors (ETRs), which form dimers and higher-order oligomers in their functional state as determined by the binding of Cu(I), a cofactor to their transmembrane helices in the ER-Golgi endomembrane system. The molecular structure and signaling mechanism of the membrane-integral sensor domain are still unknown. In this article, we report on the crystallization of transmembrane (TM) and membrane-adjacent domains of plant ethylene receptors by Lipidic Cubic Phase (LCP) technology using vapor diffusion in meso crystallization. The TM domain of ethylene receptors ETR1 and ETR2, which is expressed in E. coli in high quantities and purity, was successfully crystallized using the LCP approach with different lipids, lipid mixtures, and additives. From our extensive screening of 9216 conditions, crystals were obtained from identical crystallization conditions for ETR1 (aa 1-316) and ETR2 (aa 1-186), diffracting at a medium–high resolution of 2–4 Å. However, data quality was poor and not sufficient for data processing or further structure determination due to rotational blur and high mosaicity. Metal ion loading and inhibitory peptides were explored to improve crystallization. The addition of Zn(II) increased the number of well-formed crystals, while the addition of ripening inhibitory peptide NIP improved crystal morphology. However, despite these improvements, further optimization of crystallization conditions is needed to obtain well-diffracting, highly-ordered crystals for high-resolution structural determination. Overcoming these challenges will represent a major breakthrough in structurally determining plant ethylene receptors and promote an understanding of the molecular mechanisms of ethylene signaling.
Gender and Age Effects on the Trajectory of Depression in Opioid Users during Methadone Maintenance Treatment

Introduction Both heroin use and depression are significant health problems. Methadone maintenance treatment (MMT) can be of great benefit to heroin users. However, changes in the level of depression in heroin users during MMT are not clear. Gender and age are also important factors in the development of depression, and whether gender and age moderate changes in depression in heroin users during MMT warrants further study. This study aimed to explore: (1) the trajectory of depression in opioid users during MMT and (2) the moderating effects of gender and age on the trajectory of depression in opioid users receiving MMT. Method A total of 294 intravenous heroin users were recruited into this 9-month observational study. The level of depression was measured at the intake interview and at follow-up interviews every 3 months. A latent growth model was used to analyze the trajectory of the level of depression among the participants. Results Depression improved rapidly during the first 3 months of MMT and slowly after the first 3 months in both the female and male heroin users. There was no gender difference in the level of depression at each follow-up point. The level of depression in the female heroin users decreased faster than that in the male heroin users. In addition, the level of depression in the younger heroin users decreased faster than that in the older subjects. Conclusion Depression in female and younger heroin users improved more rapidly than in male and older subjects, respectively.
The Impact of Noise Correlation on the Single-Symbol ML Decodable Distributed STBCs

Very recently, we proposed the distributed orthogonal space-time block codes (DOSTBCs) in [1]. We showed that the DOSTBCs achieved the single-symbol maximum likelihood (ML) decodability and the full diversity order. Furthermore, we studied some special DOSTBCs, namely the row- monomial DOSTBCs, which generated uncorrelated noises at the destination. We showed that the row-monomial DOSTBCs achieved approximately twice higher bandwidth efficiency than the repetition-based cooperative strategy. However, the data-rate of the DOSTBC was not analyzed in [1]. In this paper, we consider the general DOSTBCs, which possibly generate correlated noises at the destination. We derive an upper bound of the data- rate of the DOSTBC. This upper bound is larger than that of the row-monomial DOSTBC, and hence, the DOSTBCs can potentially improve the bandwidth efficiency of the cooperative network.
Discovering causes of financial distress by combining evolutionary algorithms and artificial neural networks

In this work we compare two soft-computing methods for producing models that are able to predict whether a company is going to have book losses: artificial neural networks (ANNs) and genetic programming (GP). In order to build prediction models that can be applied to an extensive number of practical cases, we need simple models which require a small amount of data. Kohonen's self-organizing map (SOM) is a non-supervised neural network that is usually used as a clustering tool. In our case a SOM has been used to reduce the dimensions of the prediction problem. Traditionally, ANNs have been considered able to produce better classifier structures than GP. In this work we merge the capability of GP for generating classification trees and the feature extraction abilities of SOM, obtaining a classification tool that beats the results yielded using an evolutionary ANN method.
Predicting class testability using object-oriented metrics

We investigate factors of the testability of object-oriented software systems. The starting point is given by a study of the literature to obtain both an initial model of testability and existing OO metrics related to testability. Subsequently, these metrics are evaluated by means of two case studies of large Java systems for which JUnit test cases exist. The goal of This work is to define and evaluate a set of metrics that can be used to assess the testability of the classes of a Java system.
Minimizing Tension in Teams

In large organizations (e.g., companies, universities, etc.) individual experts with different work habits are asked to work together in order to complete projects or tasks. Oftentimes, the differences in the inherent work habits of these experts causes tension among them, which can prove detrimental for the organization's performance and functioning. The question we consider in this paper is the following: "can this tension be reduced by providing incentives to individuals to change their work habits? " We formalize this question in the definition of the k- AlterHabit problem. To the best of our knowledge we are the first to define this problem and analyze its properties. Although we show that k- AlterHabit is NP-hard, we devise polynomial-time algorithms for solving it in practice. Our algorithms are based on interesting connections that we draw between our problem and other combinatorial problems. Our experimental results demonstrate both the efficiency and the efficacy of our algorithmic techniques on a collection of real data.
Approximate theoretical models for TCP connections using different high speed congestion control algorithms in a multihop network

We consider a multihop network when the flows may be using TCP Reno, CUBIC or Compound. We study its performance using fluid approximations. We provide theoretical justification for these approximations. Our approximations are simple, yet can be used to obtain throughput and average window size for each TCP connection with good accuracy. We compare results obtained using fluid approximations with discrete Markov chain models in [1] and [2] and with ns2 simulations. The fluid approximation models can be seen to trade-off accuracy for simplicity.
Similar Tumor Suppressor Gene Alteration Profiles in Asbestos-Induced Murine and Human Mesothelioma

The status of tumor suppressor genes (TSGs) relevant to human malignant mesothelioma (HMM) pathogenesis was examined in cultures of mesothelioma cells from tumoral ascites developed in mice exposed to asbestos (asb) fibers. The status of the respective hortologous human genes was also investigated in 12 HMM cell cultures. Eleven primary cultures from mice hemizygous for Nƒ2 (asb-Nf2KO3/+) and 4 wild type counterparts (asb-Nf2+/+) were analyzed for mutations in Nf2, p16/Cdkn2a, p19/Arf and Trp53 genes and protein expression of p15/Cdkn2b and Cdk4. TSG alterations in both mouse and human mesothelioma cells consisted in frequent inactivation of p16/Cdkn2a, p19/Arf (or P14/ARF) and p15/Cdkn2b, co-inactivation of p16/Cdkn2a and p15/Cdkn2b and low rate of Trp53 mutations in both asb-Nf2KO3/+ and asb-Nf2+/+ mesothelioma cells. In both mouse and human mesothelioma cells, inactivation of the hortologous genes p16/Cdkn2a or P16/CDKN2A was due to deletions at the Ink4/Arf locus encompassing p19/Arf or P14/ARF, respectively. Loss of heterozygosity at the Nf2 locus was detected in 10 of 11 asb-Nf2KO3/+ cultures and Nf2 gene rearrangement in one asb-Nf2+/+ culture. These data show that the profile of TSG alterations in asbestos-induced mesothelioma is similar in mice and humans. Thus, the mouse mesothelioma model could be useful for human risk assessment, taking into account interindividual variations in genetic sensitivity to carcinogens.
Designing an Interactive Message Board as a Technology Probe forFamily Communication

In this paper, we describe the design issues and technical implementation of an interactive Family Message Board. The Family Message Board enables members of a distributed family to communicate with one another both synchronously and asynchronously via simple, pen-based, digital notes. Each household running this Java-based software can view, create, and manipulate notes in a zoomable space. The Family Message Board will be used as a “technology probe” to help us understand the communication needs of distributed families, and to help us design new devices to meet those needs.
Directed Spectral Methods Definition

Directed spectral measures quantify, in the frequency domain, directed statistical interactions between time-series variables. Most commonly, the various measures are computed based on a (linear) multi-variate autoregressive (MVAR) model of the data. The various methods quantify in different ways the strength of interaction terms in the Fourier transform of the MVAR model. While these methods are sometimes referred to as capturing ‘causal’ or ‘effective’ connectivity, they are most properly described as reflecting ‘directed functional connectivity’ (Friston et al. 2013).