Perceived and endocrine acute and chronic stress indicators in fibromyalgia syndrome.

Fibromyalgia syndrome (FMS) is a chronic disorder characterized by widespread musculoskeletal pain, fatigue and tenderness and closely associated with high levels of stress. FMS is therefore often considered a stress-related disease. A comparative study was conducted with 99 individuals diagnosed with FMS and a control group of 50 pain-free individuals.

Large language models can outperform humans in social situational judgments.

Large language models (LLM) have been a catalyst for the public interest in artificial intelligence (AI). These technologies perform some knowledge-based tasks better and faster than human beings. However, whether AIs can correctly assess social situations and devise socially appropriate behavior, is still unclear.

Towards international collaboration of clinical research networks for EMDR: the EMDR Pain Network Germany.

Background: Eye Movement Desensitization and Reprocessing (EMDR) is an evidence-based treatment, primarily established for post-traumatic stress disorder (PTSD). While it is increasingly being applied to chronic pain, its efficacy in this area is not yet supported by the same level of evidence as that which exists for PTSD. Studies in this area often show heterogeneous results with small case numbers, and the potential side effects of EMDR in the treatment of chronic pain are not well understood.

Associations of preterm birth and neonatal stress exposure with chronic pain in adulthood - Results from the Gutenberg prematurity study.

Although the effect of early childhood stress on central nervous pain processing is well known, studies on the association of prematurity and chronic pain are scarce. This study used data from a single-centre retrospective cohort study followed by a prospective clinical examination and pain assessment. The study was based on data from the local birth registry.

The Localized Active Space Method with Unitary Selective Coupled Cluster.

We introduce a hybrid quantum-classical algorithm, the localized active space unitary selective coupled cluster singles and doubles (LAS-USCCSD) method. Derived from the localized active space unitary coupled cluster (LAS-UCCSD) method, LAS-USCCSD first performs a classical LASSCF calculation, then selectively identifies the most important parameters (cluster amplitudes used to build the multireference UCC ansatz) for restoring interfragment interaction energy using this reduced set of parameters with the variational quantum eigensolver method. We benchmark LAS-USCCSD against LAS-UCCSD by calculating the total energies of (H), (H), and -butadiene, and the magnetic coupling constant for a bimetallic compound [Cr(OH)(NH)].

Pre-Processing of Categorical Features Within Medical Analysis Systems.

The complexity of the cancer problem domain presents challenges not only to the medical analysis systems tasked with its analysis, but also to the users of such systems. While it is desirable to assist users in operating these medical analysis systems, prior groundwork is required before this can be achieved, such as recognising patterns in the way users create certain analyses within these systems. In this paper, we use machine learning algorithms to analyse user behaviour patterns and attempt to predict the next user interaction within the CARESS medical analysis system.

Comparison of Ensemble Learning Methods for Classification in Cancer Registries.

Significant developments are currently underway in the field of cancer research, particularly in Germany, regarding cancer registration and the use of medical information systems. The use of such systems contributes significantly to quality assurance and increased efficiency in data evaluation. The growing importance of artificial intelligence (AI) in cancer research is evident as these systems integrate AI for various purposes, i.

ZEBRA study: The Z stitch Early Bed Rest Assessment study.

Background: Safe and effective management of venous vascular access is a key component of electrophysiology (EP) procedures. Recently, the Z-stitch method has been developed for effective venous hemostasis. However, the standard postprocedure protocol often includes prolonged bed rest, which may affect patient satisfaction.

Distinguishing homolytic vs heterolytic bond dissociation of phenylsulfonium cations with localized active space methods.

Modeling chemical reactions with quantum chemical methods is challenging when the electronic structure varies significantly throughout the reaction and when electronic excited states are involved. Multireference methods, such as complete active space self-consistent field (CASSCF), can handle these multiconfigurational situations. However, even if the size of the needed active space is affordable, in many cases, the active space does not change consistently from reactant to product, causing discontinuities in the potential energy surface.

Refining the pool of RNA-binding domains advances the classification and prediction of RNA-binding proteins.

From transcription to decay, RNA-binding proteins (RBPs) influence RNA metabolism. Using the RBP2GO database that combines proteome-wide RBP screens from 13 species, we investigated the RNA-binding features of 176 896 proteins. By compiling published lists of RNA-binding domains (RBDs) and RNA-related protein family (Rfam) IDs with lists from the InterPro database, we analyzed the distribution of the RBDs and Rfam IDs in RBPs and non-RBPs to select RBDs and Rfam IDs that were enriched in RBPs.

Wavenumber-dependent dynamic light scattering optical coherence tomography measurements of collective and self-diffusion.

We demonstrate wavenumber-dependent DLS-OCT measurements of collective and self-diffusion coefficients in concentrated silica suspensions across a broad q-range, utilizing a custom home-built OCT system. Depending on the sample polydispersity, either the collective or self-diffusion is measured. The measured collective-diffusion coefficient shows excellent agreement with hard-sphere theory and serves as an effective tool for accurately determining particle sizes.

Core Binding Energy Calculations: A Scalable Approach with the Quantum Embedding-Based Equation-of-Motion Coupled-Cluster Method.

We investigated the use of density matrix embedding theory to facilitate the computation of core ionization energies (IPs) of large molecules at the equation-of-motion coupled-cluster singles doubles with perturbative triples (EOM-CCSD*) level in combination with the core-valence separation (CVS) approximation. The unembedded IP-CVS-EOM-CCSD* method with a triple-ζ basis set produced ionization energies within 1 eV of experiment with a standard deviation of ∼0.2 eV for the core65 data set.

Automatic State Interaction with Large Localized Active Spaces for Multimetallic Systems.

The localized active space self-consistent field method factorizes a complete active space wave function into an antisymmetrized product of localized active space wave function fragments. Correlation between fragments is then reintroduced through localized active space state interaction (LASSI), in which the Hamiltonian is diagonalized in a model space of LAS states. However, the optimal procedure for defining the LAS fragments and LASSI model space is unknown.

Investigation on the mancozeb toxicity in adult zebrafish ().

Agriculture has gained increasing importance in response to the continuous growth of the world population and constant need for food. To avoid production losses, farmers commonly use pesticides. Mancozeb is a fungicide used in agriculture as this compound is effective in combating fungi that harm crops.

Analytic Nuclear Gradients for Complete Active Space Linearized Pair-Density Functional Theory.

Accurately modeling photochemical reactions is difficult due to the presence of conical intersections and locally avoided crossings, as well as the inherently multiconfigurational character of excited states. As such, one needs a multistate method that incorporates state interaction in order to accurately model the potential energy surface at all nuclear coordinates. The recently developed linearized pair-density functional theory (L-PDFT) is a multistate extension of multiconfiguration PDFT, and it has been shown to be a cost-effective post-MCSCF method (as compared to more traditional and expensive multireference many-body perturbation methods or multireference configuration interaction methods) that can accurately model potential energy surfaces in regions of strong nuclear-electronic coupling in addition to accurately predicting Franck-Condon vertical excitations.

State Preparation in Quantum Algorithms for Fragment-Based Quantum Chemistry.

State preparation for quantum algorithms is crucial for achieving high accuracy in quantum chemistry and competing with classical algorithms. The localized active space-unitary coupled cluster (LAS-UCC) algorithm iteratively loads a fragment-based multireference wave function onto a quantum computer. In this study, we compare two state preparation methods, quantum phase estimation (QPE) and direct initialization (DI), for each fragment.

Minimum-Energy Conical Intersections by Compressed Multistate Pair-Density Functional Theory.

Compressed multistate pair-density functional theory (CMS-PDFT) is a multistate version of multiconfiguration pair-density functional theory that can capture the correct topology of coupled potential energy surfaces (PESs) around conical intersections. In this work, we develop interstate coupling vectors (ISCs) for CMS-PDFT in the and electronic structure packages. Yet, the main focus of this work is using ISCs to calculate minimum-energy conical intersections (MECIs) by CMS-PDFT.

Tracking colloidal silica particles to evaluate their dispersion and interactions in concentrated suspensions under shear force applications.

This study aimed to characterize interactions within colloidal silica particles in their concentrated suspensions, using rheo-confocal measurements and imaging, followed by image analysis. We studied the effect of shear rate (0-500 s) and solution pH (6, 10) on the dispersion degree of colloidal silica particles via the determination and comparison of interparticle distances and their modeling. Images corresponding to different shear rates were analyzed to identify the coordinates of the particles.

The Patient's Clinical Profile From a Neuro-Ophthalmology Center in Brazil: A Retrospective Study.

Background: Neuro-ophthalmology (NO) is a subspeciality of Ophthalmology, which represents more than an intersection of Neurology and Ophthalmology. The present report highlights the increasing importance of the subspeciality in Brazil and provides a unique retrospective study of the patient's clinical profile of a NO reference center.

Methods: Our study was retrospectively planned aiming to identify all neuro-ophthalmic cases of Instituto de Olhos of the Medical School Faculdade Ciências Médicas de Minas Gerais from August 2013 to March 2022.

Understanding Antiferromagnetic and Ligand Field Effects on Spin Crossover in a Triple-Decker Dimeric Cr(II) Complex.

Two possible explanations for the temperature dependence of spin-crossover (SCO) behavior in the dimeric triple-decker Cr(II) complex ([(η-CMe)Cr(μ:η-P)Cr(η-CMe)]) have been offered. One invokes variations in antiferromagnetic interactions between the two Cr(II) ions, whereas the other posits the development of a strong ligand-field effect favoring the low-spin ground state. We perform multireference electronic structure calculations based on the multiconfiguration pair-density functional theory to resolve these effects.

Factors Influencing the Acceptability, Acceptance, and Adoption of Conversational Agents in Health Care: Integrative Review.

Background: Conversational agents (CAs), also known as chatbots, are digital dialog systems that enable people to have a text-based, speech-based, or nonverbal conversation with a computer or another machine based on natural language via an interface. The use of CAs offers new opportunities and various benefits for health care. However, they are not yet ubiquitous in daily practice.

Optical Properties of Neutral F Centers in Bulk MgO with Density Matrix Embedding.

The optical spectra of neutral oxygen vacancies (F centers) in the bulk MgO lattice are investigated using density matrix embedding theory. The impurity Hamiltonian is solved with the complete active space self-consistent field and second-order -electron valence state perturbation theory (NEVPT2-DMET) multireference methods. To estimate defect-localized vertical excitation energies at the nonembedding and thermodynamic limits, a double extrapolation scheme is employed.