Sclerosing angiomatoid nodular transformation (SANT) of the spleen: a case report.

SANT is a rare, non-lymphoid, benign entity, originating from the red pulp of the spleen. It is characterized by the presence of vascular nodules surrounded by a stroma of collagen fibers. It was introduced as a distinct disease entity by Martel et al in 2004, after the histopathological examination of 25 cases.

Diagnostic performance of single-lead electrocardiograms for arterial hypertension diagnosis: a machine learning approach.

Awareness and early identification of hypertension is crucial in reducing the burden of cardiovascular disease (CVD). Artificial intelligence-based analysis of 12-lead electrocardiograms (ECGs) can already detect arrhythmias and hypertension. We performed an observational two-center study in order to develop a machine learning algorithm to proactively detect arterial hypertension from single-lead ECGs.

Targeted Energy Transfer Dynamics and Chemical Reactions.

Ultrafast reaction processes take place when resonant features of nonlinear model systems are taken into account. In the targeted energy or electron transfer dimer model this is accomplished through the implementation of nonlinear oscillators with opposing types of nonlinearities, one attractive while the second repulsive. In the present work, we show that this resonant behavior survives if we take into account the vibrational degrees of freedom as well.

The circular economy through the prism of machine learning and the YouTube video media platform.

The transition to a Circular Economy (CE) is rapidly gaining ground across countries and industries. It is the means of achieving more sustainable development by adopting innovative environmentally friendly strategies and saving primary resources. There are several studies indicating the increasing public and corporate interest in the CE but still remain limited in terms of the multitude and utilization of social media data.

Revisiting the use of the EORTC QLQ-STO22 to assess health-related quality of life of patients with gastric cancer: incorporating updated treatment options and cross-cultural perspectives.

Background: The EORTC QLQ-STO22 (QLQ-STO22) is a firmly established and validated measure of health-related quality of life (HRQoL) for people with gastric cancer (GC), developed over two decades ago. Since then there have been dramatic changes in treatment options for GC. Also, East Asian patients were not involved in the development of QLQ-STO22, where GC is most prevalent and the QLQ-STO22 is widely used.

T-wave inversion through inhomogeneous voltage diffusion within the FK3V cardiac model.

The heart beats are due to the synchronized contraction of cardiomyocytes triggered by a periodic sequence of electrical signals called action potentials, which originate in the sinoatrial node and spread through the heart's electrical system. A large body of work is devoted to modeling the propagation of the action potential and to reproducing reliably its shape and duration. Connection of computational modeling of cells to macroscopic phenomenological curves such as the electrocardiogram has been also intense, due to its clinical importance in analyzing cardiovascular diseases.

Quantum neural networks for the discovery and implementation of quantum error-correcting codes.

We implement and use quantum neural networks that exploit bit-flip quantum error-correcting codes that correct bit-flip errors in arbitrary logical qubit states. We introduce conjugate layer quantum autoencoders and use them in order to restore states impacted by amplitude damping through the utilization of an approximative four-qubit error-correcting codeword. Our specific implementation avoids barren plateaus of the cost function and improves the training time.

Quantum targeted energy transfer through machine learning tools.

In quantum targeted energy transfer, bosons are transferred from a certain crystal site to an alternative one, utilizing a nonlinear resonance configuration similar to the classical targeted energy transfer. We use a computational method based on machine learning algorithms in order to investigate selectivity as well as efficiency of the quantum transfer in the context of a dimer and a trimer system. We find that our method identifies resonant quantum transfer paths that allow boson transfer in unison.

Deep learning-assisted frequency-domain photoacoustic microscopy.

Frequency-domain photoacoustic microscopy (FD-PAM) constitutes a powerful cost-efficient imaging method integrating intensity-modulated laser beams for the excitation of single-frequency photoacoustic waves. Nevertheless, FD-PAM provides an extremely small signal-to-noise ratio (SNR), which can be up to two orders of magnitude lower than the conventional time-domain (TD) systems. To overcome this inherent SNR limitation of FD-PAM, we utilize a U-Net neural network aiming at image augmentation without the need for excessive averaging or the application of high optical power.

Artificial intelligence-based opportunistic screening for the detection of arterial hypertension through ECG signals.

Objectives: Hypertension is a major risk factor for cardiovascular disease (CVD), which often escapes the diagnosis or should be confirmed by several office visits. The ECG is one of the most widely used diagnostic tools and could be of paramount importance in patients' initial evaluation.

Methods: We used machine learning techniques based on clinical parameters and features derived from the ECG, to detect hypertension in a population without CVD.

Hybrid confocal fluorescence and photoacoustic microscopy for the label-free investigation of melanin accumulation in fish scales.

Lower vertebrates, including fish, can rapidly alter skin lightness through changes in melanin concentration and melanosomes' mobility according to various factors, which include background color, light intensity, ambient temperature, social context, husbandry practices and acute or chronic stressful stimuli. Within this framework, the determination of skin chromaticity parameters in fish species is estimated either in specific areas using colorimeters or at the whole animal level using image processing and analysis software. Nevertheless, the accurate quantification of melanin content or melanophore coverage in fish skin is quite challenging as a result of the laborious chemical analysis and the typical application of simple optical imaging methods, requiring also to euthanize the fish in order to obtain large skin samples for relevant investigations.

Sclerosing angiomatoid nodular transformation of the spleen: a case report.

Sclerosing angiomatoid nodular transformation (SANT) of the spleen is an uncommon primary benign condition with specific histopathological characteristics. The majority of the patients are usually asymptomatic and present for treatment after an incidental finding on a routine abdominal imaging. The differential diagnosis includes other benign tumours, as well as primary malignancy or metastases of unknown origin.

Analysis of chaotic dynamical systems with autoencoders.

We focus on chaotic dynamical systems and analyze their time series with the use of autoencoders, i.e., configurations of neural networks that map identical output to input.

Nonlinear scattering by non-Hermitian multilayers with saturation effects.

We theoretically investigate the optical properties of a one-dimensional non-Hermitian dispersive layered system with saturable gain and loss. We solve the nonhomogeneous Helmholtz equation perturbatively by applying the modified transfer matrix method and we obtain closed-form expressions for the reflection or transmission coefficients for TM incident waves. The nonreciprocity of the scattering process can be directly inferred from the analysis of the obtained expressions.

Detection of abnormal left ventricular geometry in patients without cardiovascular disease through machine learning: An ECG-based approach.

Cardiac remodeling is recognized as an important aspect of cardiovascular disease (CVD) progression. Machine learning (ML) techniques were applied to basic clinical parameters and electrocardiographic features, in order to detect abnormal left ventricular geometry (LVG) even before the onset of left ventricular hypertrophy (LVH), in a population without established CVD. The authors enrolled 528 patients with and without essential hypertension, but no other indications of CVD.

Axitinib as a third or further line of treatment in renal cancer: a single institution experience.

Background: Kidney cancer is a lethal neoplasm that affects several thousands of people every year. Renal cell carcinoma (RCC) is the most common histologic type. Recent developments in the therapeutic approach include antiangiogenic targeted approaches and Immunotherapy.

Estimating the infection horizon of COVID-19 in eight countries with a data-driven approach.

The COVID-19 pandemic has affected all countries of the world producing a substantial number of fatalities accompanied by a major disruption in their social, financial and educational organization. The strict disciplinary measures implemented by China were very effective and thus were subsequently adopted by most world countries to various degrees. The infection duration and number of infected persons are of critical importance for the battle against the pandemic.

Lymphocytic infiltration and Chemotherapy Response Score as prognostic markers in ovarian cancer patients treated with Neoadjuvant chemotherapy.

Neoadjuvant Chemotherapy (NACT) followed by Interval Debulking Surgery (IDS) is an accepted frontline treatment in patients with advanced Epithelial Ovarian Cancer (EOC). Histopathologic assessment of tumor post NACT may provide a surrogate for response to treatment. The present study aims to characterize the pathological response and to examine its prognostic significance in these patients.

Pattern formation and chimera states in 2D SQUID metamaterials.

The Superconducting QUantum Interference Device (SQUID) is a highly nonlinear oscillator with rich dynamical behavior, including chaos. When driven by a time-periodic magnetic flux, the SQUID exhibits extreme multistability at frequencies around the geometric resonance, which is manifested by a "snakelike" form of the resonance curve. Repeating motifs of SQUIDs form metamaterials, i.

Risk for Venous Thromboembolic Events in Patients With Advanced Urinary Tract Cancer Treated With First-Line Chemotherapy.

Background: Venous thromboembolic events (VTEs) frequently occur in cancer patients. Risk assessment models (RAMs) for cancer-associated thrombosis have been proposed. However, advanced urinary tract cancer (aUTC) was not adequately represented in these models.

Ewing's sarcoma of the cervix: A case report of an unusual diagnosis in pregnancy treated with surgery, adjuvant VIDE and radiotherapy.

Ewing's sarcoma of the cervix is a rare entity and presents with considerable challenges in diagnosis and therapy. Herein, we report a case of a cervical Ewing's sarcoma presenting with FIGO stage Ib, diagnosed during the first trimester of the patient's pregnancy. Imaging with CT scans, MRI of her abdomen and PET-CT verified the locoregional extension of the tumor.

Cutaneous toxicities of antineoplastic agents: data from a large cohort of Greek patients.

Purpose: Cutaneous toxicities from novel anticancer treatments are an emerging problem in dermato-oncology. However, the prevalence of those toxicities and necessity of skin consultations are currently unknown. The purpose of our study was to perform an epidemiologic analysis of cutaneous toxicities that were referred to our cutaneous toxicity clinic in Athens, Greece.

Compact Localized States in Engineered Flat-Band [Formula: see text] Metamaterials.

The conditions leading to flat dispersionless frequency bands in truly one-dimensional parity-time ([Formula: see text]) symmetric metamaterials comprised of split-ring resonators (SRRs) arranged in a binary pattern are obtained analytically. In this paradigmatic system, in which the SRRs are coupled through both electric and magnetic dipole-dipole forces, flat-bands may arise from tailoring its natural parameters (such as, e.g.

Management of uterine sarcomas and prognostic indicators: real world data from a single-institution.

Background: Uterine sarcomas consist a heterogeneous group of mesenchymal gynecological malignancies with unclear therapeutic recommendations and unspecific but poor prognosis, since they usually metastasize and tend to recur very often, even in early stages.

Methods: We retrospectively analyzed all female patients with uterine sarcomas treated in our institution over the last 17 years. Clinico-pathological data, treatments and outcomes were recorded.