Search Results (932)

Chronic myeloid leukemia (CML) has undergone a significant shift over the past two decades, transitioning from a fatal malignancy to a chronic, highly manageable disease with near-normal life expectancy for most patients. This transformation has been driven by the development of BCR-ABL1-targeted tyrosine kinase inhibitors (TKIs), which have enabled durable disease control and deep molecular responses (DMRs) in the majority of patients with chronic-phase CML. As long-term survival outcomes have plateaued across available agents, contemporary management has shifted beyond disease suppression toward optimizing long-term safety, quality of life, and the achievement of treatment-free remission (TFR). This review summarizes current evidence on molecular monitoring strategies, the comparative efficacy and toxicity profiles of first-, second-, and third-generation TKIs, and emerging advances in response assessment. Patient-centered TKI selection is discussed in the context of cardiovascular risk, comorbidities, treatment tolerability, and survivorship goals, reflecting the growing emphasis on individualized therapy in chronic-phase CML. Molecular monitoring strategies are examined in parallel, highlighting the clinical importance of early and sustained DMRs in guiding therapeutic decisions and TFR eligibility. Although RT-qPCR remains the standard for molecular monitoring, emerging high-sensitivity techniques such as digital droplet PCR and next-generation sequencing provide complementary value by improving the detection of low-level residual disease, refining risk stratification, and enabling earlier identification of resistance. Emerging therapeutic strategies and advances in response assessment further highlight ongoing efforts to enhance the depth and durability of remission while minimizing long-term toxicity. These developments support a more precise, individualized, and outcome-driven approach to modern CML management. Full article

In this paper we present a low-noise, high-frame-rate global shutter CMOS image sensor with UHD resolution (3840 × 2160), targeting high-speed machine vision applications. The sensor (ForzaFAST581) supports video capture at up to 1141 FPS at 12 bits and 1694 FPS at 8 bits at full resolution, consuming a total power of 5.5 W. Fabricated in a 65 nm, four-metal BSI process, the imager features a 5 µm voltage-domain global shutter pixel with dual-gain capability for improved dynamic range and a read noise of 3.04 e⁻ in global shutter and 2.15 e⁻ in rolling shutter mode for high-gain at maximum frame rate operation. For compact camera integration and low power consumption, the sensor is designed to stream video through 16 CML data ports, each operating at 7.44 Gbps, achieving a total aggregate throughput of 119 Gbps. Additionally, the sensor supports selectable output bit depths—8-bit, 10-bit, and 12-bit—allowing frame rate optimization based on application-specific requirements. Full article

With the intensification of global climate change, environmental issues such as soil salinization and drought have exerted an increasingly prominent impact on plants. Tibetan peach (Amygdalus mira), a rare native tree species of the genus Amygdalus in the Rosaceae family, possesses extremely strong tolerance to cold, drought, and disease stress. In the previous study, we found that the protein abundance of a calcium-binding protein, AmCML24, was significantly upregulated in Tibetan peach under drought stress, leading us to hypothesize that it plays an important role in the molecular mechanisms underlying plant responses to abiotic stresses. Therefore, this study focuses on AmCML24, aiming to preliminarily characterize the stress-tolerant function of AmCML24 and explore its biological role in plant tolerance to saline–alkali and drought stresses. Results demonstrated that AmCML24 responds to multiple abiotic stresses. Yeast and Arabidopsis thaliana lines overexpressing AmCML24 exhibited enhanced tolerance to NaCl, NaHCO₃, and mannitol stresses, with a significant upregulation in the expression of stress-responsive genes. This study lays a solid foundation for deciphering the stress regulatory network of Tibetan peach and elucidating the biological function of AmCML24, while also providing a scientific basis for the genetic improvement, exploitation, and utilization of Tibetan peach germplasm resources. Full article

Calmodulin-like proteins (CMLs) are key mediators of plant calcium signaling and participate in abiotic stress responses, but their functions in potato remain poorly understood. Here, we systematically identified 62 StCML genes in potato via genome-wide analysis, which were phylogenetically clustered into seven clades and unevenly distributed across 12 chromosomes. Synteny analysis indicated that tandem and segmental duplications drove StCML family expansion, while promoter cis-element analysis suggested their involvement in phytohormone signaling and stress responses. Transcriptomic data showed StCMLs exhibited tissue-specific expression (high in roots, flowers, stamens) and were transcriptionally induced by drought, salt, and abscisic acid (ABA). Heterologous overexpression of StCML50 in Arabidopsis enhanced drought tolerance, as evidenced by improved germination, root elongation, and survival compared to wild-type. Physiologically, StCML50 overexpression increased proline accumulation, boosted antioxidant enzyme (SOD, CAT, POD) activities, and reduced malondialdehyde (MDA) levels under drought. Additionally, transgenic lines showed increased ABA sensitivity. This study provides insights into the potato CML gene family’s evolution and regulatory mechanisms, offering a valuable genetic resource for potato stress tolerance improvement. Full article

Estimating how crop yield responds to site-specific nitrogen (N) fertilization is essential for maximizing yield potential under variable field conditions. However, classical Machine Learning (ML) approaches applied to observational farm data primarily focus on yield prediction and often fail to recover causal N response due to confounding arising from non-random fertilizer application. In this study, we develop and evaluate a Causal Machine Learning (CML) framework to estimate heterogeneous N treatment effects under real commercial rice-farming conditions in the Axios River Plain, Greece. The proposed approach combines Double Machine Learning (DML) with remote sensing, soil, climatic, and management data to adjust for confounding and identify causal relationships between N inputs, Leaf Nitrogen Concentration (LNC), and yield. A doubly robust (DR) learner is used to estimate yield sensitivity to N at key agronomic thresholds, while a Causal Forest model leverages LNC to assess crop physiological N status. Results demonstrate that the CML-based framework outperforms conventional XGBoost predictive models in identifying field plots that are responsive to additional N. By integrating causal effect estimation with plant-status information, the proposed decision support system identifies zones where yield gains can be achieved through targeted N increases while avoiding overfertilization in non-responsive areas. Full article

With the increasing frequency extreme weather events associated with climate change, real-time monitoring of rainfall intensity is critical for water resource management, disaster warning, and other applications. Traditional methods, such as ground-based rain gauges, radar, and satellites, face challenges like high costs, low resolution, and monitoring gaps. This study proposes a novel real-time rainfall intensity monitoring method based on deep learning and audio signal processing, using acoustic features from rainfall to predict intensity. Conducted in the semi-arid region of Northwest China, the study employed a custom-designed sound collection device to capture acoustic signals from raindrop-surface interactions. The method, combining multi-feature extraction and regression modeling, accurately predicted rainfall intensity. Experimental results revealed a strong linear relationship between sound pressure and rainfall intensity (r = 0.916, R² = 0.838), with clear nonlinear enhancement of acoustic energy during heavy rainfall. Compared to traditional methods like CML and radio link techniques, the acoustic approach offers advantages in cost, high-density deployment, and adaptability to complex terrain. Despite some limitations, including regional and seasonal biases, the study lays the foundation for future improvements, such as expanding sample coverage, optimizing sensor design, and incorporating multi-source data. This method holds significant potential for applications in urban drainage, agricultural irrigation, and disaster early warning. Full article

Endophytic fungi enhance plant growth and stress resilience, yet their molecular roles in the roots of the endangered tree Phoebe bournei remain unclear. A comparative RNA-seq analysis was performed on root transcriptomes from wild, endophyte-colonized adult trees (OT) and axenically grown seedlings (ST). Unmapped reads were analyzed against the NCBI nucleotide (NT) database using BLASTN (v2.17.0), revealing Rhizophagus irregularis as the predominant endophytic fungus. Differential expression analysis identified 5891 DEGs, which were significantly enriched in pathways related to plant–pathogen interactions, phenylpropanoid biosynthesis, plant hormone signal transduction, and MAPK signaling. Key upregulated genes included PbMPK3, PbCML42, PbCML41.2, and PbGSTU28, suggesting enhanced ROS scavenging, calcium signaling, and defense activation. RT-qPCR validation confirmed the transcriptomic trends for selected genes. Our findings reveal that root endophytic fungi modulate a coordinated network involving immune priming, phytohormone regulation, and redox homeostasis, thereby supporting root development and enhancing resistance to biotic and abiotic stresses in P. bournei. This study provides foundational molecular insights into beneficial plant–endophyte interactions and identifies candidate genes that are valuable for the conservation and breeding of this threatened species. Full article

Background: Macrocytosis commonly develops during imatinib therapy, but its relationship with cytogenetic and molecular outcomes in chronic myeloid leukemia (CML) remains unclear. We investigated whether increases in mean corpuscular volume (MCV) during imatinib treatment are associated with response depth and treatment persistence. Methods: In this retrospective study, we analyzed 101 adults with chronic-phase CML treated with a stable imatinib dose of 400 mg/day for at least 12 months. Patients with conditions that could confound MCV (hydroxyurea exposure, megaloblastic anemia, hypothyroidism, chronic liver disease, alcoholism) were excluded. Complete cytogenetic response (CCyR) and major molecular response (MMR) were assessed by conventional karyotyping and the BCR-ABL1 International Scale, respectively. Increased MCV was defined as MCV > 100 fL after six months of therapy, persisting thereafter. Associations between MCV dynamics, response, and switching to second-generation tyrosine kinase inhibitors were evaluated. Results: Twenty patients (20%) developed increased MCV. Overall, 86 patients (85%) achieved CCyR and 70 (69%) achieved MMR. All patients with increased MCV attained CCyR, compared with 66 of 81 (81%) without MCV elevation (p = 0.037), while MMR rates were 90% versus 64% (p = 0.030). During a median follow-up of 69 months, treatment modification was required in 1 of 20 (5%) patients with increased MCV versus 25 of 81 (31%) in the non-increased group (p = 0.018). Conclusions: MCV elevation during imatinib therapy is associated with deeper molecular response and reduced need for treatment modification. MCV dynamics may serve as an inexpensive pharmacodynamic marker to support risk assessment and guide monitoring in chronic-phase CML. Full article

Background: Honeybees sustain vital ecological roles through foraging behavior, which provides pollination services and is likely regulated by dopamine signaling coupled to brain energy metabolism. However, the genetic and metabolic mechanisms underlying this regulation remain unclear. Methods: We treated honeybee workers with the dopamine receptor agonist bromocriptine and employed an integrative approach, combining liquid chromatography–mass spectrometry (LC–MS) metabolomics with single-nucleus RNA sequencing (snRNA-seq). Results: Metabolomics revealed increased levels of N6-carboxymethyllysine (CML) and a coordinated shift in central carbon metabolites, including higher glucose, pyruvate, and lactate within glycolysis, and ribose-5-phosphate in the pentose phosphate pathway (PPP). Integration with transcriptomics showed heterogeneous responses: glial cells exhibited higher glycolysis pathway scores and upregulated hexokinase expression compared to neurons, whereas major PPP enzymes were upregulated in both glial and neuronal subsets. Conclusions: These findings suggest that dopamine receptor activation is associated with altered whole-brain metabolic profiles and concurrent, cell-type-specific upregulation of glycolytic and PPP enzyme genes, particularly in glia. This study characterizes these neuro-metabolic associations, offering insights into the cellular and metabolic basis of foraging behavior in worker bees. Full article

The current-mode logic (CML) driver has evolved alongside integrated circuit (IC) technology. Its typical structure contains a tail current source, differential amplifying transistors, and load resistors. It is widely used in modern optical transceivers and other serial link transceivers, and is compatible with various processes, including CMOS, SiGe BiCMOS, and InP DHBT. The basic performance indicators of CML driver include gain, bandwidth, power, and total harmonic distortion (THD). For different application scenarios, different tail currents and load resistance are required. Nowadays, as the performance requirements for drivers in various applications continue to increase, more techniques need to be employed to balance high speed, high output amplitude, high linearity, and low power, such as bandwidth expansion techniques, linearity improvement techniques, and gain control techniques. In this review, the electrical characteristics of basic CML circuits are highlighted and compared with other interface level standards. The advancement of CML drivers is summarized. Emerging CML structures and performance enhancement technologies are introduced and analyzed. Design considerations are concluded in terms of the challenges faced by high-speed drivers. The review provides comparative study and comprehensive reference for designers. Full article

Metallic engineered nanomaterials (ENMs) have enormous technological potential and are increasingly applied across different fields and products. However, substances (including ENMs) can be detrimental to the environment and human health, thus requiring systematic testing to uncover potential hazardous effects (in compliance with REACH). Although hazard testing traditionally involves the use of animal experiments, recent years have seen a shift towards in silico modeling. High-quality data is required for in silico modeling, which is frequently not readily available for ENMs. Vast amounts of data have been published in literature but they are unstructured and scattered across numerous sources. To mitigate the limitations in data availability, we have compiled and created a nanotoxicity dataset based on published literature. The compiled dataset focuses mainly on acute in vivo endpoints conducted in a laboratory setting using metallic nanomaterials. The data extracted from literature include material information, physico-chemical properties, experimental conditions, endpoint information, and literary meta-data. The dataset presented here is useful for meta-analysis or in silico modeling purposes. Full article

Background: The tyrosine kinase inhibitors (TKIs) asciminib, bosutinib, dasatinib, imatinib, nilotinib, and ponatinib have been approved for chronic myelogenous leukemia (CML) therapy. However, pharmacovigilance reports associated with these drugs are neither consistent nor homogenous, with reports of pulmonary toxicity, which could limit their utilization. To better clarify TKIs’ pulmonary risk, we used the European database EudraVigilance to conduct a study on adverse events suspected to be caused by the TKIs asciminib, bosutinib, dasatinib, imatinib, nilotinib, and ponatinib when used for CML therapy. Methods: Suspected adverse reactions to TKIs in the EudraVigilance database (2020–2024) coming from European countries and the United Kingdom were analyzed and compared through a disproportionality analysis. Results: The most frequent alerts concerned the respiratory disorders “pleural effusion” (PE) and “pulmonary arterial hypertension” (PAH) in relation to dasatinib and bosutinib use. Among the TKIs, the prescription of dasatinib is associated with a higher occurrence of PE and PAH, while the prescription of bosutinib induces PE at a minor frequency that nonetheless carries a significant risk for PAH, occurring more often in women. Conclusions: The results indicate that respiratory disorders induced by the TKIs dasatinib and bosutinib need to be diagnosed in a timely manner, and suggest that caution should be taken when prescribing these TKIs to patients affected by CML and pulmonary comorbidities. Full article

Background/Objectives: Conventional workflows, peripheral blood smears, and bone marrow assessment supplemented by LDI-PCR, molecular cytogenetics, and array-CGH, are expert-driven in the face of biological and imaging variability. Methods: We propose an AI pipeline that integrates convolutional neural networks (CNNs) and transfer learning-based models with two explainable AI (XAI) approaches, LIME and Grad-Cam, to deliver both high diagnostic accuracy and transparent rationale. Seven public sources were curated into a unified benchmark (66,550 images) covering ALL, AML, CLL, CML, and healthy controls; images were standardized, ROI-cropped, and split with stratification (80/10/10). We fine-tuned multiple backbones (DenseNet-121, MobileNetV2, VGG16, InceptionV3, ResNet50, Xception, and a custom CNN) and evaluated the accuracy and F1-score, benchmarking against the recent literature. Results: On the five-class task (ALL/AML/CLL/CML/Healthy), MobileNetV2 achieved 97.9% accuracy/F1, with DenseNet-121 reaching 97.66% F1. On ALL subtypes (Benign, Early, Pre, Pro) and across tasks, DenseNet121 and MobileNetV2 were the most reliable, achieving state-of-the-art accuracy with the strongest, nucleus-centric explanations. Conclusions: XAI analyses (LIME, Grad-CAM) consistently localized leukemic nuclei and other cell-intrinsic morphology, aligning saliency with clinical cues and model performance. Compared with baselines, our approach matched or exceeded accuracy while providing stronger, corroborated interpretability on a substantially larger and more diverse dataset. Full article

Background/Objectives: Tyrosine kinase inhibitors (TKIs) have transformed the treatment of chronic myeloid leukemia (CML), yet emerging evidence indicates an increased risk of vascular adverse events, particularly peripheral artery disease (PAD). Reliable biomarkers for early detection of TKI-related vascular toxicity are still lacking. Methods: A cross-sectional study was conducted on 78 patients with chronic-phase CML treated at Dr. Soetomo General Hospital, Surabaya. PAD was confirmed using ankle–brachial index. Serum oxidized low-density lipoprotein (OxLDL) and interleukin-10 (IL-10) levels were measured using ELISA. Results: PAD was detected in 20% of subjects. The PAD group showed significantly higher OxLDL, lower IL-10, and a markedly elevated OxLDL/IL-10 ratio (all p < 0.001). OxLDL remained independently associated with PAD after adjustment (adjusted OR = 1.132, 95% CI 1.020–1.255, p = 0.019). OxLDL/IL-10 ratio yielded a good diagnostic value (sensitivity 87.5% and specificity of 88.7%). Conclusions: Elevated OxLDL and an increased OxLDL/IL-10 ratio are associated with PAD in CML patients receiving TKI therapy and demonstrated a good diagnostic performance for early detection of TKI-induced vascular toxicity. Full article

This manuscript presents the development of an electrochemical biosensor designed to detect K-562 chronic myeloid leukemia (CML) cells. The biosensor was made of highly oriented pyrolytic graphite (HOPG), functionalized with -OH and -COOH groups by surface etching with strong acids, and subsequently coated with modified titanium dioxide (TiO₂-m). TiO₂-m is TiO₂ modified during its synthesis process using carbon nanotubes functionalized with -OH and -COOH groups. These changes improve the electron transfer kinetics and physicochemical properties of the electrode surface. TiO₂-m improves the sensitivity and selectivity towards leukemic cells. The detection process involved three stages: cell culture, cell adhesion onto the TiO₂–m electrode, and measurement of the electrochemical signal. Fluorescence microscopy and SEM-EDS confirmed cell adhesion and pseudopod formation on the TiO₂-m surface, which is an important finding because K-562 cells are typically nonadherent. Cyclic voltammetry (VC) and differential pulse voltammetry (VDP) demonstrated rapid and sensitive detection of leukemic cells within the concentration range of 6250 to 1,000,000 cells/mL, achieving high reproducibility and strong linearity (R² = 98%) with a detection time of 25 s. The VC and VDP demonstrated rapid and sensitive detection of leukemic cells over a concentration range of 6250 to 1,000,000 cells/mL, achieving adequate reproducibility and stable linearity (R² = 98%), with a detection time of 25 s. These results indicate that the TiO₂-m biosensor is a promising platform for the rapid and efficient electrochemical detection of leukemia cells. Full article