Browse Articles

CDC7 is a targetable regulator of advanced prostate cancer

Abstract Prostate cancer is estimated to contribute to over 35,000 deaths of men residing in the United States, with the majority fatality due to metastatic disease. CDC7 is a kinase that regulates DNA replication and is found elevated during neuroendocrine transdifferentiation in lung and prostate cancer. In this study, we demonstrate that CDC7 is highly expressed in treatment-resistant prostate cancer, with even higher levels observed in treatment-resistant prostate cancer with neuroendocrine phenotype (NEPC). We further identify CDC7 as a critical regulator of prostate tumorigenesis. Downregulation of CDC7 significantly reduces prostate cancer cells growth and invasion in vitro and silencing CDC7 suppresses prostate tumor growth in vivo . Furthermore, we demonstrate that the inhibition of CDC7 using TAK-931, a selective CDC7 inhibitor, significantly reduces the proliferation, migration, and invasion of aggressive prostate cancer cells. TAK-931 treated prostate cancer cells exhibit an abnormal cell cycle profile, suggesting that CDC7 inhibition induces replication stress and promotes apoptosis. Collectively, our findings demonstrate that CDC7 is a regulator of tumor progression in prostate cancer and represents new therapeutic target in advanced prostate cancer.

Serum-free differentiation platform for the generation of B lymphocytes and natural killer cells from human CD34+ cord blood progenitors

Abstract Pre-clinical research on B and NK cell development relies on murine stromal cell-based systems with reduced physiological relevance and clinical applicability. A serum-free, fully humanized co-culture system utilizing human bone marrow-derived mesenchymal stromal cells (BM-MSCs) was developed to differentiate CB-CD34+ cells towards B and NK cell lineages. Differentiation dynamics were monitored via flow cytometry, with immunophenotypic analysis tracking progression from progenitors to mature cells. The system generated CD19+ IgM+ immature B cells and CD56+ CD16+ NK cells, recapitulating fetal stages of human lymphopoiesis. Serum-free media conditions ensured reproducibility and high overall yield of CD19+ B (35 ± 5.32%) and CD56+ NK (28.46 ± 7.01%) cell progenitors. Flow cytometry identified distinct population peaks, confirming temporal control over differentiation. This clinically relevant platform addresses the limitations of traditional models by providing a more physiologically accurate human microenvironment. The serum-free system supports applications in disease modeling, genotoxic compound screening, and mutational studies of hematopoiesis. By enabling scalable production of B and NK cells it aims to accelerate translational research for immunodeficiencies, cancer immunotherapy, and hematopoietic disorders.

The top US health director who stood up for science — and was fired

Microwave assisted synthesis and bioactive potential of folic acid functionalized tellurium nanoparticles (FA@Te NPs) against HeLa cancer cells

Parametric optimization of graphite powder-mixed electrical discharge machining of Ni-Cr dental alloy by response surface methodology

Effect of early prophylactic heparin use on prognosis in critically ill patients with acute pancreatitis: a retrospective cohort study

Development of head-trunk coordination measures for assessing sensorimotor function in laboratory and natural settings using wearable sensors

Abstract Stabilization of the head in space is important for postural and locomotion control. Disruptions in head-trunk coordination can impair functional performance during aging, pathophysiology, or exposure to altered sensory environment states such as spaceflight. Monitoring head-trunk coordination could aid in understanding the risks associated with sensorimotor impairment. The present study evaluated a custom algorithm developed from parameters of head-trunk coordination obtained from wearable sensors. Task performance of healthy adults during standard laboratory tasks both with and without physical restriction via a neck brace were assessed to develop the algorithm and motion thresholds. The algorithm was applied to 12 blinded 4-hr datasets to evaluate the reliability and sensitivity of the measures for identifying altered head-to-trunk coordination when a neck brace was worn during daily activities in a natural setting. The primary head-to-trunk coordination metrics showing high detection accuracy were the root mean square deviation between the angular velocity signals of the head and trunk, followed by the difference in the magnitude orientation. Additionally, the coherence of angular velocity along the X and Z global axes demonstrated good detection sensitivity. The present work lays the foundation for future applications, particularly in monitoring impaired head-trunk coordination in natural settings to provide valuable insights for rehabilitation.

Dynamic evolution of intracortical and corticomuscular connectivity during reach-and-grasp movement planning and execution

Unveiling leaf rust resistance introgressed from non-progenitor wild species Aegilops kotschyi into hexaploid wheat

Hydrogeological deciphering of the poorly gauged karstic Mount Hermon Aquifer

Zmynd10 drives centriole biogenesis and multiciliogenesis through the transcriptional regulation of E2f4

Impact of 85 kHz versus 125 kHz SHIFT OCTA scan speeds on image quality in retinal diseases and diagnostic reliability of choroidal neovascular membranes

Abstract The purpose of the study was to compare Optical Coherence Tomography Angiography (OCTA) scan speeds of 85 kHz and 125 kHz with respect to image quality, diagnostic reliability, and scan time in patients with retinal diseases. In this prospective cohort study, OCTA images were obtained at both scan speeds in 70 eyes from 40 patients with retinal diseases. Masked expert graders evaluated qualitative parameters including clinical utility, artifacts, and overall image quality. Quantitative parameters including scan time, Heidelberg Q-score, and OCTA-Q score were recorded. In 46 eyes with visible choroidal neovascular membrane in the avascular layer of OCTA, AngioTool (Image J) was used to assess vessel percentage area, vessel junction density, average vessel length, and E-Lacunarity. Acquisition speed of 125 kHz OCTA was significantly faster than that of 85 kHz. There were no statistically significant differences in AngioTool parameters between the two protocols. 125 kHz was significantly better than 85 kHz for image quality with fewer noise artefacts and vessel projection artefacts. In conclusion, 125 kHz SHIFT OCTA offers comparable to better image quality to the 85 kHz OCTA with significantly faster acquisition, potentially improving clinical workflow without compromising diagnostic reliability.

Evaluation of netrin 1 as a new biomarker in the differentiation of psoriatic arthritis from psoriasis

Cyber-resilient machine learning framework for accurate individual load forecasting and anomaly detection in smart grids

Abstract With the evolution of smart grids, accurate and secure predictions of the electricity load become crucial for efficient energy management and reliability. In this paper, a scalable and cyber-resilient methodology for electricity consumption forecasting on individual smart meter level based on machine learning and anomaly detection schemes is proposed. The proposed technique utilizes K-MEANS Clustering and Neural Networks (KMEANS–NN) to enhance Individual Load Forecasting (ILF) with reduced computational complexity and high prediction accuracy. A Principal Component Analysis based One-Class Support Vector Machine (PCA–OCSVM) model is employed as an Anomaly Detection Scheme (ADS) to identify the false data injection attacks in smart meter telemetry. The system uses five months of real-world data from $$\:\text{2,089}$$ smart meters gathered under the supervision of Electrical Distribution Sector (EDS) of Suez Canal Authority (SCA) in Egypt. KMEANS–NN strategy reduces significantly MAAPE by up to $$\:25.6\%$$ and cuts computational time from days to minutes. It improves forecasting accuracy across four proposed models: ARIMA, CTREE, MLP and NNETAR. To assess the cyber-security profile, $$\:50\%$$ of the dataset is orchestrated with scaling, ramping and random cyber-attack simulation. Proposed ADS achieves $$\:99.3\%$$ overall accuracy, $$\:100\%$$ sensitivity, $$\:98.62\%$$ precision, $$\:98.6\%$$ specificity and F1-score of $$\:\:0.9896$$ , whereas it’s $$\:100\%$$ accurate on clean data. This integrated model offers accurate, efficient, and secure load forecasting presenting good potential for its deployment in large-scale smart grid environments.

Tuning of the band gap and suppression of metallic phase by ca doping in La1 − xCaxMnO3 manganite nano-particles

Development and application of formation damage mitigation system for heavy oil reservoir

Integrated high-fidelity preparation and analysis of photonic two-qubit states for quantum network nodes

Abstract The realisation of quantum networks requires local quantum information processing at the network nodes and highly efficient transmission of quantum information across the network. Integrated photonics, based on silicon-on-insulator, is a promising platform for quantum network nodes, as it supports low-loss propagation of telecom wavelength photons, making it compatible with existing optical fibre networks. Here, we present a silicon-on-insulator integrated photonic chip, capable of bidirectional operation, enabling the preparation of arbitrary single- and two-qubit states, and performing full quantum state tomography on up to two qubits. Using our chip, we obtain preparation fidelities above $${97}{\%}$$ for on-chip prepared Bell states coupled into optical fibres. Furthermore, we demonstrate that we can distribute entanglement between network nodes by preparing a two-qubit cluster state on the first node and performing full quantum state tomography on the second node, achieving a fidelity of 90.0(16)%. This result proves that our approach allows the distribution of entanglement from one chip to another. The potential of bidirectional operation makes our circuit a versatile node in telecom quantum networks, both functioning as a sender and receiver unit, a key element for the deployment of fully photonic multi-purpose quantum networks.

Impact of a novel ultra-processed foods and drinks diet on metabolism and behaviour in adolescent female and male rats

Carbon fixation performance and the stability surroundings of Serratia sp. isolated from karst

Stagnation-point flow of a Sisko nanofluid over a stretching surface with heat generation and nano-transport phenomena

Abstract The present investigation focuses on the transient magnetohydrodynamic (MHD) behaviour of the stagnation-point flow of a Sisko nanofluid past a stretching surface, highlighting the interactive influence of internal heat generation and nano-scale transport mechanisms. The study integrates the rheological complexity of the Sisko model with nanoparticle motion induced by Brownian diffusion and thermophoresis, both of which substantially modify the fluid’s momentum, thermal, and solutal layers. Through appropriate similarity transformations, the governing nonlinear partial differential equations are transformed and parameterized into a set of coupled ordinary differential equations, subsequently solved using MATLAB’s bvp4c routine. A systematic evaluation of controlling parameters including the Sisko material constant, Brownian diffusion, thermophoretic strength, and heat generation coefficient—has been performed to elucidate their respective impacts on velocity, temperature, and concentration distributions. The findings reveal that nano-scale diffusion processes intensify both thermal and solutal gradients, whereas internal heat generation augments the thermal boundary layer thickness. This study delivers deeper theoretical understanding of non-Newtonian nanofluid dynamics and underscores its significance for enhanced heat transfer applications in polymer extrusion, coating systems, and advanced thermal manufacturing operations.