Christoph Rehbach¹, Patrick A. H. Ehm^2,*

BIOCELL, Vol.50, No.5, 2026, DOI:10.32604/biocell.2026.075170 - 13 May 2026

Abstract Despite improved overall prognosis, the treatment of high-risk acute lymphoblastic leukemia (ALL) remains challenging due to the toxicity of intensive polychemotherapy and the limited efficacy of antibody-targeted therapies beyond cluster of differentiation 20 and 22 (CD20 and CD22). ALL is driven not only by genetic alterations but also by profound epigenetic dysregulation, including promoter hypermethylation that also silences surface receptor genes. This epigenetic repression can reduce the efficacy of targeted immunotherapies and contribute to relapse. Epigenetic reprogramming with DNA demethylating agents (e.g., decitabine) has the potential to restore the expression of key B cell receptors… More >

Gyuri Han^#, Yun Hee Jeong^#, Ga Eun Kim, Jong-Sup Bae^*

BIOCELL, Vol.50, No.5, 2026, DOI:10.32604/biocell.2026.075139 - 13 May 2026

Abstract Objectives: Plant-derived bioactive molecules are increasingly recognized as valuable therapeutic resources for managing diverse pathological conditions, particularly those involving vascular inflammation. This study aimed to determine whether veratramine (VRT), a naturally occurring steroidal alkaloid found in Veratrum species of the Liliaceae family, attenuates LPS-induced vascular and pulmonary inflammation by upregulating heme oxygenase-1 (HO-1) and modulating the Nrf2, nuclear factor (NF)-κB, and signal transducer and activator of transcription (STAT1) signaling pathways. Methods: The study assessed the modulatory effects of VRT on HO-1, cyclooxygenase-2 (COX-2), and inducible nitric oxide synthase (iNOS) in LPS-activated human umbilical vein endothelial cells… More > Graphic Abstract

Sebastián Jaurreteche^1,2,*, María Luana Brajkovic², María Victoria Del Rosal², Graciela Venera³, Carlos Daniel De la Vega Elena⁴

BIOCELL, Vol.50, No.5, 2026, DOI:10.32604/biocell.2026.073790 - 13 May 2026

Abstract Protein misfolding has emerged as a central mechanism in the pathogenesis of human kidney diseases. Normally, proteins achieve their native conformation through highly regulated folding processes in the endoplasmic reticulum (ER) and cytoplasm, assisted by molecular chaperones and quality-control pathways. However, genetic variants, environmental stressors, or cellular overload can destabilize this system, resulting in unfolded or misfolded proteins that trigger aggregation, amyloid formation, endoplasmic reticulum stress, and activation of the unfolded protein response (UPR). These events may ultimately lead to loss of function, gain of toxic function, and apoptosis. This review summarizes the structural basis… More >

Andrea De Matthaeis¹, Laura Rehak^2,*, Maria Bianchi³, Rossana Putzulu³, Nicola Piccirillo^3,4, Giulio Maccauro¹

BIOCELL, Vol.50, No.5, 2026, DOI:10.32604/biocell.2026.073783 - 13 May 2026

Abstract For over two decades, mesenchymal stem cells (MSCs) have been recognised as the cornerstone of orthobiologic treatments for musculoskeletal diseases. However, clinical evidence increasingly indicates that MSC engraftment in inflamed tissues is minimal and transient, with effects mainly driven by paracrine and immunomodulatory mechanisms induced by macrophage efferocytosis. This evolving paradigm emphasises the immune system as the central orchestrator of tissue repair. Peripheral blood mononuclear cells (PBMNCs) have emerged as potent effectors of regenerative inflammation, mediating apoptotic cell clearance through efferocytosis, facilitating the transition of macrophages from pro-inflammatory (M1) to reparative (M2) phenotypes, and releasing… More >

Thanh Tuan Nguyen¹, Cuong Nguyen Dinh Hoa^2,3,*

Intelligent Automation & Soft Computing, Vol.41, pp. 1-24, 2026, DOI:10.32604/iasc.2026.078344 - 12 May 2026

Abstract Accurate crude oil price forecasting is critical for global economic stability but remains an exceptionally challenging task due to the data’s complex, non-linear, and non-stationary nature. Deep learning models like LSTMs are widely favored. However, the dominant research trend currently focuses on increasingly complex hybrid and ensemble architectures. These models often suffer from high computational overhead, intricate tuning processes, and potential overfitting, raising critical questions about their necessity. In this paper, we challenged the assumption that complexity is required for high performance by proposing and evaluating a streamlined 1D-CNN model. We conducted a comprehensive evaluation… More >

Chirag Devendrakumar Parikh^*

Journal on Internet of Things, Vol.8, pp. 109-125, 2026, DOI:10.32604/jiot.2026.077412 - 12 May 2026

Abstract Secure IoT ecosystems are based on the notion that device authentication is reputable. Traditional approaches typically use software identifiers or stored cryptographic keys, which can be cloned, copied, or modified by physical access or supply-chain interference. The current paper presents a hardware fingerprinting system that is based on compliance to enhance the strength of the authentication of the IoT device, that is, to connect physical device properties with organized conformity practices. The tool exploits intrinsic electrical and manufacturing differences in parts to produce device-specific fingerprints and compares these fingerprints with compliance processes, including component validation, More >

Akash Garg^*

Journal on Artificial Intelligence, Vol.8, pp. 273-298, 2026, DOI:10.32604/jai.2026.079401 - 12 May 2026

Abstract As cyber threats continue to evolve in scale and sophistication, the need for intelligent and adaptive security mechanisms has become increasingly urgent. Intrusion Detection Systems (IDS) are critical components in safeguarding computer networks from malicious activities. This review paper presents a comprehensive analysis of recent advancements in deep learning-based IDS, examining various architectures such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), autoencoders, and generative adversarial networks (GANs). The study compares traditional intrusion detection techniques with modern deep learning approaches, highlighting their strengths, limitations, and suitability for real-world deployment. Special attention is given to… More >

Jianping Wu¹, Nian Li^2,*, Libin Dong³, Ping Zhang⁴

Journal on Artificial Intelligence, Vol.8, pp. 259-271, 2026, DOI:10.32604/jai.2026.075753 - 12 May 2026

Abstract This paper presents a static fusion framework that enhances object detection by integrating camera and LiDAR-based detection results. The proposed method focuses on associating 2D candidate bounding boxes from a camera detector with 3D candidate boxes from a LiDAR detector using an Intersection over Union (IoU)-based matching approach. To enhance the quality of 2D detection, we refine the baseline Cascade R-CNN detector by incorporating a dual self-attention mechanism into both the backbone and the region proposal network (RPN), resulting in the DA-Cascade R-CNN. This enhancement strengthens the network’s ability to detect small or distant objects More >

Shan Yuan^1,2, Fei Wang^2,*, Jinping Zhang^2,*, Yuxin Jiang², Kaibo Gu², Chenhao Qiao², Yutong Bai², Jie Yu², Quan Chen¹, Dedi Han³

Chalcogenide Letters, Vol.23, No.4, 2026, DOI:10.32604/cl.2026.082805 - 09 May 2026

Abstract Sodium metal batteries stand as a highly promising electrochemical energy storage system; however, their commercialization is severely impeded by challenges such as anode dendrite formation, the shuttle effect of highly reactive intermediates at the cathode, electrode volume expansion, and interfacial instability. Owing to their high electronic conductivity, high theoretical specific capacity, and superior sodiumphilic affinity, tellurium and its tellurides have emerged as pivotal functional materials for enhancing the performance of sodium metal batteries. This study reviews the advancements in their applications within sodium metal batteries, elaborates rational design strategies carbon-based composites, alloying, and heterostructure construction More >

Mohsin Sayeed^1,*, O. P. Singh¹, Vishal Singh Chandel², Azam Raza³, Kamal Batcha Mohamed Ismail⁴, Mayur Khan⁵, Navshad Alam^6,7, Mohammad Shariq⁸

Chalcogenide Letters, Vol.23, No.4, 2026, DOI:10.32604/cl.2026.079721 - 09 May 2026

Abstract An eco-friendly one-pot hydrothermal method was developed to synthesize molybdenum disulfide/graphene oxide (MoS₂/GO) nanocomposites for high-performance supercapacitor applications. X-ray diffraction (XRD) analysis confirmed the presence of the MoS₂ crystalline phase, with reduced peak intensities upon GO incorporation, indicating suppressed crystallite growth. Scanning electron microscopy (SEM) revealed rod-like MoS₂ structures uniformly distributed across layered GO sheets, and energy-dispersive spectroscopy (EDS) confirmed the presence of Mo, S, C, and O elements. Raman and FTIR analyses verified strong interfacial interactions between MoS₂ and GO. Brunauer–Emmett–Teller (BET) measurements revealed a mesoporous structure with a specific surface area of ~31.7 m² g⁻¹ and… More >