Browse Articles

Enhanced value of chest computed tomography radiomics features in breast density classification

The novel HRD motif kinase SPE-60 is required for sperm development and motility in Caenorhabditis elegans

Abstract Sexual reproduction requires sperm development, activation and motility. Many of these post-meiotic processes remain incompletely understood. We identified the gene spe-60, which encodes a tau-tubulin kinase with a conserved catalytic HRD motif. Localisation via immunostaining reveals that SPE-60 is present in sperm and dynamically colocalises with membranous organelles (MOs), that store factors essential for activation and fertility. spe-60 null mutants are sterile due to immotile sperm that undergo normal MO-plasma membrane fusion but fail to extend normal pseudopods essential for motility and fertilisation. Furthermore, mutant sperm exhibit arrested spermatocyte development. The functional loss observed in spe-60 null sperm is phenocopied by sperm carrying a CRISPR/Cas-mediated point mutation within the HRD motif. Genetic epistasis places SPE-60 downstream of the serine/threonine kinase SPE-6 in the canonical sperm activation pathway. Thus, SPE-60 is required for sperm development and motility, but not MO fusion. These findings suggest that the HRD-containing kinase SPE-60 fulfils a dual function as a key evolutionarily conserved factor.

Co-administration of Spirulina and L-carnitine preserves ovarian reserve in a rat model of premature ovarian insufficiency via SIRT1 regulation of oxidative stress, inflammation, and apoptosis

Abstract This study aimed to assess the possible consequences of spirulina (SP) and/or L-carnitine (L-car) on the prevention of primordial follicular reserve depletion and the preservation of ovarian follicular structure and function in a rat model of premature ovarian insufficiency (POI). Forty healthy adult female Sprague-Dawley albino rats were randomly assigned into five equal-sized groups (n = 8): normal control, DOX group (2.5 mg/kg i.p.), SP group (500 mg/kg intragastric), L-car group (250 mg/kg i.p.), and SP + L-car group in the same previous doses. In comparison to the DOX group, administration of either SP or L-car significantly increased serum E2 and AMH levels along with a significant decrease in the FSH and LH levels (p < 0.05). The oxidative stress was significantly reduced. Ovarian expressions of NF-κB, iNOS, FOXO1, P53, and caspase-3 decreased significantly, while SIRT1, STAR, CYP17A1, HSD17B3, Nrf2, and mtDNA increased significantly. Histology revealed histoarchitecture improvement as the mean % of atretic follicles and degenerated corpora lutea was significantly reduced (p < 0.05). The combined treatments synergistically improved the parameters studied more than either treatment alone. The molecular docking results revealed the ability of both n-hexadecanoic acid and L-carnitine to activate SIRT1 and subsequent antioxidant, anti-inflammatory, and anti-apoptotic pathways. This ovoprotective effect is suggested to be mediated through activation of different SIRT1-mediated protective signaling pathways that remodel ovarian redox status, inflammation, and apoptosis, which may strengthen the potential role of SP and L-car as a chemotherapy adjuvant, reducing the negative health effects of early menopause after cancer therapy.

4D flow MRI enhances prototype testing of a total artificial heart

Abstract The shortage of donor hearts urges the need for total artificial hearts (TAHs). Existing TAHs cause complications like infection, stroke, and hemolysis due to adverse flow dynamics, but assessment of flow in a TAH is challenging. We investigated the feasibility of using 4D flow magnetic resonance imaging (MRI) to assess blood flow dynamics in the left side of a pulsatile TAH under representative physiological conditions. A prototype of a pulsatile TAH was modified using powder bed fusion and fused filament fabrication 3D printing techniques to function in an MRI environment. The TAH connected to an MRI compatible mock circulatory loop allowed variable physiological conditions (i.e. heart rate 80, 105, 120 bpm) and was scanned with two different velocity encodings. Flow patterns and turbulent kinetic energy were measured with high accuracy in a short measurement time and analyzed. Stasis and viscous energy loss in the artificial heart were found to be similar to healthy native hearts. Elevated turbulent kinetic energy was found in several areas, but values were well below those found in patients with valvular disease. Using 4D flow MRI in combination with 3D printing can facilitate assessment of flow dynamics in TAHs and enable a rapid iterative design process.

Retraction Note: Rechallenge therapy versus tyrosine kinase inhibitor (TKI) for advanced metastatic colorectal cancer: a retrospective study

Unraveling cooperative and competitive interactions within protein triplets in the human interactome

Abstract Knowledge of protein–protein interactions (PPIs) is essential for understanding cellular function, yet most network analyses focus on binary interactions. Higher-order motifs such as protein triplets can reveal cooperative or competitive relationships but are difficult to distinguish systematically. We present a computational framework to classify protein triplets in the human protein interaction network (hPIN) as cooperative or competitive. The hPIN was embedded in hyperbolic space using the LaBNE + HM algorithm, and a Random Forest classifier was trained on structurally validated triplets from Interactome3D, achieving high accuracy (AUC = 0.88). Angular and hyperbolic distances were key predictive features. Predicted cooperative triplets were enriched in paralogous partners, indicating that paralogs often bind together to a shared protein using non-overlapping surfaces. The model proved to be effective when tested on a new dataset. AlphaFold 3 modeling supported these predictions, showing that cooperative partners bind at distinct sites, while competitive ones overlap. Our results demonstrate the value of hyperbolic geometry for capturing functional organization in protein complexes.

Analytical construction and visualization of nonlinear waves in the (2+1) dimensional Kadomtsev-Petviashvili-Sawada-Kotera-Ramani equation with stability analysis

Abstract In this study, we investigate the (2+1)-dimensional Kadomtsev–Petviashvili–Sawada–Kotera–Ramani (KPSKR) equation, a physically significant model describing nonlinear wave phenomena in higher-dimensional spaces. Utilizing the improved modified extended tanh-function method, we derive a diverse spectrum of exact analytical solutions. These include bright solitons, singular solitons, singular periodic waves, and hyperbolic function solutions. The physical characteristics and dynamical behaviors of the obtained solutions are further elucidated through comprehensive two-dimensional and three-dimensional graphical visualizations, offering insight into the complex wave structures governed by the KPSKR equation. The results highlight the versatility of the proposed method and the rich nonlinear dynamics inherent in the model.

Real-time detection of Wi-Fi attacks using hybrid deep learning models on NodeMCU

Abstract This paper presents a real-time, lightweight system for detecting Wi-Fi deauthentication (DA) attacks that uses the NodeMCU ESP8266 microcontroller for live packet sniffing and feature extraction. Tailored for low-power IoT environments, the system combines the sequential learning capabilities of Long short-term memory (LSTM), Gate recurrent unit (GRU), and Recurrent neural network (RNN) with the interpretability of logistic regression (LR). These hybrid models analyze Wi-Fi traffic in real time to detect anomalous behavior based on key metrics such as Received Signal Strength indicator (RSSI), DA, packet count, and Signal noise ratio (SNR), which are also displayed live on an OLED screen. The proposed framework uniquely integrates hybrid temporal deep learning with interpretable classification through (LR) in an ultra-low-cost embedded data acquisition setup through NodeMCU, addressing a gap in existing intrusion detection research that often focuses on either cloud-based processing or non-interpretable model. The system was trained and validated on a dataset of over 5,600 labeled samples collected under varied network conditions. Among the evaluated models, GRU_LR achieved the highest accuracy (96%) and demonstrated superior performance in identifying minority-class threats. By combining explainable AI with cost-effective embedded sensing, this work delivers a practical and transparent intrusion detection approach that can be readily adapted to diverse IoT and wireless security contexts.

Correction: Impact of acute exercise on performance and physiological stress during simulated firefighter occupational tasks

An environmental green factorial design/assisted spectrofluorimetric technique for quantitation of citicoline in pharmaceutical dosage form and wastewater

Abstract A novel, sensitive, and straightforward spectrofluorimetric method was developed for the quantitative determination of citicoline in pharmaceutical formulations and wastewater. The technique depends on the efficient derivatisation of the primary amino group of citicoline with O-phthalaldehyde (OPA) and N-acetylcysteine (NAC) in borate buffer (pH 11), yielding a highly fluorescent derivative. The fluorescence intensity was measured at 425 nm with an excitation wavelength of 341 nm. Experimental parameters affecting the derivatisation reaction were thoroughly optimised. Under optimal conditions, the method exhibited a linear response over the concentration range of 50.0–300.0 ng/mL, with an excellent correlation coefficient (R2 = 0.9942). The limits of detection (LOD) and quantification (LOQ) were 6.4 ng/mL and 19.5 ng/mL, respectively. The approach demonstrated high accuracy and precision, with per cent recovery values close to 100% and a relative standard deviation (RSD) of 0.512%, confirming its reliability. Validation was done in agreement with ICH Q2(R1) guidelines, and statistical comparison with previously reported approaches indicated no significant difference in performance. The sustainability of the method was studied using the analytical greenness tools confirms the method’s eco-friendly profile. Collectively, these contributions advance drug bioavailability while promoting a more efficient and sustainable analytical framework.

Advanced real-time detection of acute ischemic stroke using YOLOv12, YOLOv11, and YOLO-NAS: a comparative study for multi-class classification

Abstract Acute ischemic stroke (AIS) remains a leading cause of mortality and disability worldwide, demanding diagnostic tools that are both accurate and fast for timely intervention. This study presents a comparative evaluation of three state-of-the-art object detection models-YOLOv12, YOLOv11, and YOLO-NAS-for multi-class AIS detection in magnetic resonance imaging (MRI). The dataset, comprising four categories (Normal, PD-Patient, Acute Ischemic Stroke, and Control), was preprocessed with normalization, resizing, and augmentation, then split into training (70%), validation (20%), and testing (10%). Models were trained and evaluated on identical data, with performance measured by precision, recall, mean average precision at IoU 0.5 (mAP@50), and inference speed. YOLOv11 achieved the highest mAP@50 (98.5%) and balanced precision (95.4%) and recall (96.6%), making it the most reliable across classes. YOLOv12 performed comparably (mAP@50 98.3%, precision 95.2%, recall 96.0%) with slightly slower inference, while YOLO-NAS offered the fastest speed (154 FPS) but lower precision (76.3%. Results highlight the trade-offs between detection accuracy and processing speed, providing guidance for selecting YOLO-based architectures suited to specific clinical workflows such as emergency stroke care. The real-time implementation, accessible via Roboflow, demonstrates the feasibility of deploying these models for rapid, automated AIS detection in clinical settings.

Optimizing adaptive neuro-fuzzy inference system model based Chaotic Harris Hawks algorithm for stock prediction

Abstract Artificial intelligence (AI) has become increasingly prevalent in the financial sector, particularly for predicting stock market movements. Due to the efficient market hypothesis, forecasting stock prices remains a challenging task, as prices are primarily influenced by fluctuating supply and demand. This study introduces an optimized Adaptive Neuro-Fuzzy Inference System (ANFIS) integrated with a Chaotic Harris Hawks Optimization (ChHHO) algorithm to enhance the accuracy of stock price predictions. The ChHHO method improves search space exploration and mitigates the risk of convergence to local optima, thereby enhancing predictive performance. This study is motivated by the need to improve the precision of stock price predictions, which are often hindered by the non-linear and chaotic nature of financial data. By combining ANFIS with the chaotic Harris Hawks Optimization, we aim to develop a model that addresses these challenges effectively. The proposed ANFIS-ChHHO model is evaluated on EGX index stock data using metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Standard Deviation (SD), and Theil’s U. Results demonstrate that the ANFIS-ChHHO model outperforms traditional methods in prediction accuracy.

Retraction Note: Fe3O4@void@C-Schiff-base/Pd yolk-shell nanostructures as an effective and reusable nanocatalyst for Suzuki coupling reaction

Analytical wave solutions in thermoelastic media with temperature-dependent properties via IMETF method

Abstract This study delivers an in-depth analytical investigation of exact wave solutions derived within the context of the Three-Phase-Lag (3PHL) generalized thermoelasticity model, explicitly incorporating the temperature dependence of material properties. By applying the Improved Modified Extended Tanh Function (IMETF) method, the research addresses the governing equations that describe the coupled interaction between thermal and mechanical fields in solids. A central feature of this work is the inclusion of temperature-sensitive material parameters, which play a crucial role in modifying thermoelastic responses under a variety of thermal and mechanical loading scenarios. Unlike traditional approaches, the IMETF method extends the classical tanh-function technique by introducing a more flexible solution structure capable of capturing a richer set of waveforms. This improved methodology facilitates the derivation of diverse exact analytical solutions, each governed by distinct free parameters. These include hyperbolic, singular hyperbolic, exponential, Weierstrass elliptic, and bell-shaped solitary wave solutions. Each solution class offers unique physical insights into wave propagation behavior within temperature-dependent thermoelastic media. The analytical results not only deepen the theoretical understanding but also uncover critical features of wave interaction, dispersion, and attenuation in materials governed by the 3PHL model. To further support and illustrate these findings, the paper includes detailed graphical visualizations of key physical quantities such as stress tensor components, displacement fields, and temperature distributions. These visual results serve to highlight the influence of the temperature dependence on the wave dynamics.

Sustainable supply chain practices of local versus international hotels: multiple case studies in Egypt

Abstract This study examines the adoption of sustainable supply chain practices (SSCPs) among three hotel categories: international chain hotels, 5-star local chains, and 4-star local chains located in Egypt. It aims to identify the drivers, barriers, and variations in the implementation of these practices. A qualitative multi-case study methodology was employed, involving in-depth interviews with managers at nine hotels. The study also presents a theoretical framework developed from stakeholder theory that illustrates how stakeholder pressures and organizational capacities drive or hinder the adoption of SSCPs and how these practices contribute to broader sustainability objectives. Significant variations were observed in SSCPs. International chains implement advanced practices such as comprehensive waste management and energy-efficiency programs. 5-star local chains focus on cost-saving initiatives and basic recycling, while 4-star local chains primarily adopt simple waste reduction and local sourcing. Differences in barriers also exist: 4-star local chains face more financial and knowledge limitations, while international chains face additional challenges related to supplier engagement and infrastructure. Hotel owners and managers can enhance sustainability by providing staff training, fostering collaboration with suppliers, and strategically allocating resources. Such activities are crucial for local chains with limited resources. This research fills gaps in the literature by exploring SSCPs in a developing-country context and integrating stakeholder theory to uncover both normative and instrumental drivers of SSCPs. It presents a conceptual framework that links SSCPs with drivers, barriers, and outcomes, providing a practical guide for hotels to enhance their sustainability.

Correction: Increased risk of lung cancer in individuals with preserved ratio impaired spirometry: a nationwide cohort study

Heart rate variability response of intensity-matched strength training dependent on body position in females: a pilot randomized crossover study

Abstract Heart rate variability (HRV), as an indicator of autonomic control, has been rarely studied during strength training application. This study investigates the acute HRV responses to intensity-matched resistance exercises, targeting similar muscle groups but performed in different body positions. Fourteen healthy females (21.6 ± 2.0 years) performed a 3-repetition maximum test (3-RM) for the squat movement in the Smith machine (SM, upright) and the leg press (LP, seated). During two subsequent visits, they randomly completed two exercise sessions in SM and LP (two sets of 10 repetitions at 50% 3-RM). HRV was assessed continuously (via ECG) throughout the interventions. At pre-exercise, the Root Mean Square of Successive Differences (RMSSD) and RR intervals (RRI) were significantly higher for the LP condition. Alpha1 of Detrended Fluctuation Analysis (DFAa1) was significantly higher with SM at rest. During exercise sessions, the LP condition revealed significantly reduced RMSSD (∆exercise: SM -1.19 ± 14.57 ms vs. LP -22.23 ± 22.46 ms; p = .013) and higher RRI (p < .001). No differences were observed for DFAa1. The changes between pre- and post-exercise for RMSSD and DFAa1 showed no differences between LP and SM conditions; however, RRI was significantly reduced for SM (p = .008). Within the conditions, RMSSD decreased significantly from pre- to post with SM (p 0.008) but not with LP (p = 0.271). Squats within the SM condition led to increased vagal withdrawal both at rest and after exercise, probably due to orthostatic stress. While exercising, the differences in autonomic regulation are less noticeable. Future analyses should examine the body position-dependent HRV responses to post-exercise hypotension.

Publisher Correction: Predicting coronary heart disease with advanced machine learning classifiers for improved cardiovascular risk assessment

Correction: Elucidating the mechanisms of phosphorus accumulation and use efficiency in açaí palm plants at different cultivation ages

Knowledge and Awareness of Medical Certificate of Cause of Death in Medical Undergraduate Students at a Tertiary Care Hospital

Background: The Medical Certificate of Cause of Death is not just a legal formalitybut the backbone of accurate public health surveillance and policy, yet error rates as high as 50–60% threaten the integrity of national health data and decisionmaking. Addressing persistent gaps in knowledge and practice among medical undergraduates is crucial to ensure reliable mortality statistics and effective healthcare planning for the nation’s future. Objectives: To evaluate medical undergraduates’ knowledge, awareness, and practical competence regarding the purpose, legal signi𿿿cance, correct completion, guidelines, and common errors of the Medical Certi𿿿cate of Cause of Death, andtoidentify gaps in these areas. Materials and Methods: This cross-sectional study was conducted among third year,𿿿nal year, and Compulsory Rotatory Medical Internship (CRMI) students, at Chettinad Hospital and Research Institute using a structured, self-administered online questionnaire to assess knowledge and awareness regarding the Medical Certi𿿿cate of Cause of Death. Data were analyzed with SPSS version 29, and thical approval was obtained from the Institutional Ethics Committee. Results: While all surveyed medical undergraduates correctly identi𿿿ed he xpansion andlegalimportance ofthe MCCD, signi𿿿cant knowledge gaps persisted