Browse Articles

Synthesis and evaluation of quinolinvinyl-phenoxy-1,2,3-triazole-acetamide hybrids against breast cancer

Analysis of the impact of crises tuberculosis incidence in Ukraine amid pandemics and war

Real-time peri-operative microcalcification detection in superficial breast tissues

Abstract Surgical management of ductal carcinoma in situ (DCIS), particularly in cases involving suspicious morphology and orientation of microcalcifications, remains a primary treatment option. However, the lack of real-time technical assistance in the form of an intraoperative surgical tool for detection of microcalcifications in the resection margins presents a significant challenge. In the context of breast conserving surgery, ex-vivo imaging of excised breast tissues slices from 12 patients was conducted. By employing a cross-polarized multispectral microcamera setup for tissue visualization an imaging depth of up to 2 mm was achieved. The microcamera provides the clinician with a clear color image with magnification allowing features down to 50 μm to be seen on the resection surface. Mammography images were used for accurate cross-correlation, enabling the identification of microcalcifications in the microcamera images. Detection efficacy of microcalcifications in microcamera images was notably influenced by both calcification clustering and distribution depth within the tissue. Calcifications within the 2 mm range were detected through their distinct optical manifestations in relation to the adjacent tissues. Four independent reviewers—two medical and two technical—achieved an average sensitivity of 77.8%, specificity of 80.0%, and overall accuracy of 79.0%. This study demonstrates the potential of an integrated microcamera and cross-polarized setup for non-invasive, real-time detection of microcalcifications in superficial breast tissues. By focusing on the superficial 2 mm, this approach shows promising results and offers substantial opportunities for future research and clinical applications.

Association of insulin-like growth factor 1 and metabolic parameters with mild subclinical hypothyroidism in obese boys

Abstract The aim of this study was to investigate the relationship of insulin-like growth factor-1 (IGF-1) and mild subclinical hypothyroidism (MSH) in obese boys and to assess whether the presence of MSH exacerbates cardiovascular risk factors in obesity. This study collected cross-sectional dataset covering 141 obese boys and 47 healthy non-obese boys. The obese group was further subdivided into two groups based on their serum Thyroid Stimulating Hormone (TSH) levels: the MSH group (n = 47) and the non-MSH group (n = 94). The MSH group exhibited significantly lower IGF-1 standard deviation score (IGF-1 SDS) and significantly higher Body Mass Index standard deviation score (BMI SDS) compared to the non-MSH group. Additionally, the MSH group demonstrated elevated triglycerides (TG) and gamma-glutamyl transferase (GGT) levels relative to the non-MSH group, and the incidence of non-alcoholic fatty liver disease (NAFLD) and metabolic syndrome (MS) were also higher in the MSH group than in the non-MSH group. The results of multivariable logistic regression analysis indicated that lower IGF-1 SDS and higher BMI SDS are strongly associated with MSH in obese boys, independently of systolic blood pressure (SBP), diastolic blood pressure (DBP), alanine aminotransferase (ALT), GGT and uric acid. These findings underscore the clinical utility of IGF-1 SDS and BMI SDS as potential biomarkers for identifying MSH-related cardiovascular risks in obese pediatric populations, warranting targeted screening and intervention strategies.

Evaluation of the psychometric properties of the cardiac distress inventory in Iranian patients with heart disease

Diverse solitons wave structures for coupled NLSEs in birefringent fibers with higher nonlinearities using the modified extended mapping algorithm

Green synthesis of silver nanoparticles from pomegranate peel and their application in PVA-based nanofibers for coating minced meat

Development and validation of a model for predicting the risks for delayed onset of lactogenesis stage II for Chinese pregnant women

Quantitative proteomic analysis of the protective effect exerted by alliin on ox-LDL-injured HUVECs

Generic multidimensional economic environmental operation of power systems using equilibrium optimization algorithm

Abstract The economic emission load dispatch (EELD) problem is one of the main challenges to power system operators due to the complexity of the interconnected power systems and the non-linear characteristics of the objective functions (OFs). Therefore, the EELD problem has attracted significant attention in the electric power system because it has important objectives. Thus, this paper proposes the equilibrium optimization algorithm (EOA) to solve the EELD problem in electrical power systems by minimizing the total fuel cost and emissions, considering system and operational constraints. The OFs are optimized with and without considering valve point effects (VPE) and transmission system loss. The multi-OF, which aims to optimize these objectives simultaneously, is considered. In the proposed EOA, agents are particles and concentrations that express the solution and position, respectively. The proposed EOA is evaluated and tested on different-sized standard test systems having 10, 20, 40, and 80 generation units through several case studies. The numerical results obtained by the proposed EOA are compared with other optimization techniques such as grey wolf optimization, particle swarm optimization (PSO), differential evolution algorithm, and other optimization techniques in the literature. To show the reliability of the proposed algorithm for solving the considered OFs on a large-scale power system with and without considering different practical constraints such as VPE, ramp-rate limits (RRL), and prohibited operating zones (POZs) of generating units, the proposed EOA is evaluated and tested on the 140-unit test system. Also, the proposed multi-objective EOA (MOEOA) successfully acquires the Pareto optimal front to find the best compromise solution between the considered OFs. Also, the statistical analysis and the Wilcoxon signed rank test between the EOA and other optimization techniques for solving the EELD problem are performed. From numerical results, the total fuel cost obtained without considering VPE using the proposed EOA is reduced by 0.1414%, 0.1295%, 0.6864%, 5.8441% than the results of PSO, with maximum savings of 150 $/hr, 78 $/hr, 820 $/hr, and 14,730 $/hr for 10, 20, 40, and 80 units, respectively. The total fuel cost considering VPE is reduced by 0.0753%, 0.2536%, 2.8891%, and 3.6186% than the base case with maximum savings of 80 $/hr, 158 $/hr, 3610 $/hr, 9230 $/hr for 10, 20, 40, and 80 units, respectively. The total emission is reduced by 1.7483%, 12.8673%, and 7.5948% from the base case for 10, 40, and 80 units, respectively. For the 140-unit test system, the total fuel cost without and with considering VPE, RRL, and POZs is reduced by 6.4203% and 7.2394%, than the results of PSO with maximum savings of 107,200 $/hr and 126,400 $/hr. The total emission is reduced by 2.5688% from the base case. The comparative studies show the superiority of the EOA for the economic/environmental operation of the power system by solving the EELD problem with more accuracy and efficiency, especially as the system size increases.

Screen shooting resistant watermarking based on cross attention

Multidimensional Scale of Motives for Postponing Parenthood (MSMPP-18): Development, factorial structure and psychometric properties

Evaluation of the accuracy of a low-cost external tocodynamometer in a pilot study in Malawi

Uterine contraction monitoring during labor has been linked to improved maternal outcomes. However, performing this monitoring can be challenging for financial and logistical reasons in low resource settings. This proof-of-concept study aimed to compare the accuracy of a low cost external tocodynamometer we developed to that of a commercially available external tocodynamometer. In total, 60 patients with anticipated vaginal deliveries at a hospital in Blantyre, Malawi were enrolled. Both the research device and the commercial device were secured to the patients, and traces were recorded simultaneously from each device. Trace pairs were split into 10 minute segments, and contraction locations were independently annotated on a selection of 75 contemporaneous trace pairs from 38 out of 60 patients by two expert clinicians. In total, 484 contractions were marked on the research device, and 465 contractions were marked on the commercially available device, 312 of which were marked consistently on both devices. The average consistency of marked contractions on the same device between the two observers was 0.89 for the research device compared with 0.84 for the commercially available device. The average consistency between the two devices using a 10-patient rolling average increased from 0.50 at the beginning of the study to 0.64 at the end. The annotated traces from the two devices suggested the same clinical management 72% of the time. The research device displayed reasonable agreement with the commercially available tocodynamometer in detecting contractions. The increase in the measured consistency over the course of the study suggests that improving usability of the device to ensure better positioning on the patient could result in improved performance. Further studies assessing the accuracy and usability of the device are needed.

A novel pythonic paradigm for image encryption using axis-aligned bounding boxes

Robust performances of a nocturnal long-term ECG algorithm for the evaluation of sleep apnea syndrome: A pilot study

Obstructive sleep apnea-hypopnea syndrome (OSAHS) is one of the most common sleep disorders affecting nearly one billion of the global adult population, making it a major public health issue. Even if in-lab polysomnography (PSG) remains the gold standard to diagnose OSAHS, there is a growing interest to develop new solutions with more convenient at home devices enhanced with AI-based algorithms for the detection of sleep apnea. This retrospective study aimed to assess the performances of a new method based on nocturnal long-term electrocardiogram signal to detect apneas and hypopneas, in patients who performed attended in-lab PSG. After assessing the quality of the ECG signal, the new method automatically detected apneas and hypopneas using dedicated machine learning algorithm. The agreement between the new ECG-based detection method and the standard interpretation of PSG by a sleep clinician was determined in a blind manner. Eighty-five exams were included into the study with a mean bias between the proposed method and the scorer of 3.5 apneas-hypopneas/hour (/h) (95% CI -48.1 to 55.1). At a threshold of 15/h, sensibility and specificity were 93.3% and 66.7% respectively, and positive and negative predictive values were 87.5% and 80%, respectively. The proposed method using nocturnal long-term electrocardiogram signals showed very high performances to detect apneas and hypopneas. Its implementation in a simple ECG-based device would offer a promising opportunity for preliminary evaluation of patients suspected or at-risk of OSAHS.

A recombinant BCG with surface-displayed antigen induces humoral and cellular immune responses

Adaptive mechanism-based grey wolf optimizer for feature selection in high-dimensional classification

Feature Selection (FS) is a crucial component of machine learning and data mining. Its goal is to eliminate redundant and irrelevant features from a datasets, thereby enhancing the classifier's performance. The Grey Wolf Optimizer (GWO) is a well-known meta-heuristic algorithm rooted in swarm intelligence. It is widely used in various optimization problems due to its fast convergence and minimal parameter requirements. However, in the context of solving high-dimensional classification problems, GWO’s global search capability is limited, and it is susceptible to getting trapped in local optima. To address this, we introduce an Adaptive Mechanism-based Grey Wolf Optimizer (AMGWO) for FS in high-dimensional classification. This approach encompasses a novel nonlinear parameter control strategy to balance exploration and exploitation effectively, thereby preventing the algorithm from converging prematurely. Additionally, an adaptive fitness distance balancing mechanism is proposed to prevent premature convergence and enhance search efficiency by selecting high-potential solutions. Lastly, an adaptive neighborhood mutation mechanism is designed to adjust mutation intensity adaptively during the search process, allowing AMGWO to more effectively find the global optimum. To validate the proposed AMGWO method, we assess its performance on 15 high-dimensional datasets and compare it with the original GWO and five of its variants in terms of classification accuracy, feature subset size, and execution speed, thus confirming the superiority of AMGWO.

Effectiveness of a culturally adapted online video module for enhancing parental hearing aid management skills in a quasi-experimental study

The impact of serological testing implementation on tick-borne encephalitis detection in Poland

Introduction Tick-borne encephalitis virus (TBEV) infections remain underreported in Poland, leading to inadequate public awareness of the potential severity of the disease and its preventive measures. Aim This study aims to assess the incidence of tick-borne encephalitis (TBE) in non-endemic regions of Poland by analyzing serum or cerebrospinal fluid (CSF) samples from patients with neuroinfections of unknown origin. Materials and Methods In this study, 29 departments specializing in neuroinfections were involved. Hospitals were chosen from regions classified as non-endemic with limited TBE reporting. Patients treated between April 1, and December 31, who had neuroinfections of unknown origin, were enrolled. Their CSF or serum samples underwent serological diagnosis of TBE using the Virotech ELISA kit at the Immunoserology Laboratory of the Medical University of Białystok. In addition, we used questionnaires to collect clinical and epidemiological data from patients, Results Among 766 patients, 124 exhibited serum or CSF antibodies against TBEV. None of them were vaccinated against TBE. The highest positivity rates were observed in Małopolskie (31%), Świętokrzyskie (24%), and Dolnośląskie (22%) voivodeships. In contrast, the Kujawsko-Pomorskie (2%), Pomorskie (3%), and Zachodniopomorskie (7.5%) voivodeships showed the lowest ratios. All patients reported their place of residence as a potential source of infection, some also mentioning outdoor activities, travel, work, and unpasteurized dairy consumption. Conclusions This study reveals a notable incidence of TBE infections in patients with nonspecific neuroinfections residing in regions historically seen as non-endemic. These findings emphasize the need for improved reporting and educational initiatives to raise awareness of the risk of TBE.

Quantization-based chained privacy-preserving federated learning