Variable Factor Research Articles

Assessment of Variability and Genetic Factors among High Heritable Traits of Juglans regia (Walnut) from North Western Himalayan Regions

Assessment of Variability and Genetic Factors among High Heritable Traits of Juglans regia (Walnut) from North Western Himalayan Regions

Evaluating the Impact of Elevated Temperature on Melia dubia: Insights into Climate Change Resilience and Adaptation

The consequences of climate change extended beyond temperature shifts, encompassing more extreme weather events, increased carbon di oxide enabling some plants to tolerate environmental stresses, and shifts in precipitation patterns,. Climate change manifests through alterations in the mean and variability of various properties, persisting for extended periods, often decades or longer, either due to natural variability or human-induced factors. The increase in green house gas emissions results from fossil fuel energy production, industrial activities, transportation, agriculture, construction, deforestation, and land-use changes. Plant height plays a pivotal role in the growth and development of plant species. Elevated temperature levels have been observed to enhance plant productivity, with variying impacts based on the growth stage and species response to the environment, independent of climate changes. Melia dubia is an economically important tree species grown throughout the world and the morphological, physiological and biochemical characteristics to variying air temperature is discussed in this paper

Predicting the in vivo developmental toxicity of fenarimol from in vitro toxicity data using PBTK modelling-facilitated reverse dosimetry approach

In vitro methods are widely used in modern toxicological testing; however, the data cannot be directly employed for risk assessment. In vivo toxicity of chemicals can be predicted from in vitro data using physiologically based toxicokinetic (PBTK) modelling-facilitated reverse dosimetry (PBTK-RD). In this study, a minimal-PBTK model was constructed to predict the in-vivo kinetic profile of fenarimol (FNL) in rats and humans. The model was verified by comparing the observed and predicted pharmacokinetics of FNL for rats (calibrator) and further applied to humans. Using the PBTK-RD approach, the reported in vitro developmental toxicity data for FNL was translated to in vivo dose-response data to predict the assay equivalent oral dose in rats and humans. The predicted assay equivalent rat oral dose (36.46 mg/kg) was comparable to the literature reported in vivo BMD10 value (22.8 mg/kg). The model was also employed to derive the chemical-specific adjustment factor (CSAF) for interspecies toxicokinetics variability of FNL. Further, Monte Carlo simulations were performed to predict the population variability in the plasma concentration of FNL and to derive CSAF for intersubject human kinetic differences. The comparison of CSAF values for interspecies and intersubject toxicokinetic variability with their respective default values revealed that the applied uncertainty factors were adequately protective.

Plasma Proteome-Based Test for First-Line Treatment Selection in Metastatic Non-Small Cell Lung Cancer.

Current guidelines for the management of metastatic non-small cell lung cancer (NSCLC) without driver mutations recommend checkpoint immunotherapy with PD-1/PD-L1 inhibitors, either alone or in combination with chemotherapy. This approach fails to account for individual patient variability and host immune factors and often results in less-than-ideal outcomes. To address the limitations of the current guidelines, we developed and subsequently blindly validated a machine learning algorithm using pretreatment plasma proteomic profiles for personalized treatment decisions. We conducted a multicenter observational trial (ClinicalTrials.gov identifier: NCT04056247) of patients undergoing PD-1/PD-L1 inhibitor-based therapy (n = 540) and an additional patient cohort receiving chemotherapy (n = 85) who consented to pretreatment plasma and clinical data collection. Plasma proteome profiling was performed using SomaScan Assay v4.1. Our test demonstrates a strong association between model output and clinical benefit (CB) from PD-1/PD-L1 inhibitor-based treatments, evidenced by high concordance between predicted and observed CB (R2 = 0.98, P < .001). The test categorizes patients as either PROphet-positive or PROphet-negative and further stratifies patient outcomes beyond PD-L1 expression levels. The test successfully differentiates between PROphet-negative patients exhibiting high tumor PD-L1 levels (≥50%) who have enhanced overall survival when treated with a combination of immunotherapy and chemotherapy compared with immunotherapy alone (hazard ratio [HR], 0.23 [95% CI, 0.1 to 0.51], P = .0003). By contrast, PROphet-positive patients show comparable outcomes when treated with immunotherapy alone or in combination with chemotherapy (HR, 0.78 [95% CI, 0.42 to 1.44], P = .424). Plasma proteome-based testing of individual patients, in combination with standard PD-L1 testing, distinguishes patient subsets with distinct differences in outcomes from PD-1/PD-L1 inhibitor-based therapies. These data suggest that this approach can improve the precision of first-line treatment for metastatic NSCLC.

On the nature of two-photon transitions for a collection of molecules in a Fabry-Perot cavity.

We investigate the effect of a cavity on nonlinear two-photon transitions of a molecular system and we analyze how such an effect depends on the cavity quality factor, the field enhancement, and the possibility of dephasing. We find that the molecular response to strong light fields in a cavity with a variable quality factor can be understood as arising from a balance between (i) the ability of the cavity to enhance the field of an external probe and promote multiphoton transitions more easily and (ii) the fact that the strict selection rules on multiphoton transitions in a cavity support only one resonant frequency within the excitation range. Although our simulations use a classical level description of the radiation field (i.e., we solve Maxwell-Bloch or Maxwell-Liouville equations within the Ehrenfest approximation for the field-molecule interaction), based on experience with this level of approximation in the past studies of plasmonic and polaritonic systems, we believe that our results are valid over a wide range of external probing.

Актуальные проблемы эпидемиологии офтальмологической заболеваемости среди молодежи России и Центрального федерального округа.

Indicators of primary morbidity of the eyes and their appendages in adolescents aged 15–17 years and young people, in particular among students of higher educational institutions, increase annually due to increased visual stress as risk factors. The purpose of the work is to identify current problems in the epidemiology of ophthalmological morbidity among young people in the Russian Federation and the Central Federal District. Materials and methods. A theoretical analysis of the literature on the epidemiology of ophthalmic diseases in young people and a search for statistical data on the epidemiology of ophthalmic diseases was carried out. To assess the dynamics of epidemiological indicators, an increase calculation was carried out. Results. The increase in the incidence of visual organs in adolescents per 100 thousand children aged 15–17 years from 2000 to 2021 was +47.9%, and from 2018 to 2019 the increase in the incidence of myopia was +9.2%. In the structure of diseases for adolescents, it is pathologies of the visual organs that lead, and 40% of students have visual impairments, the detection of which increases by 3–7% annually, while the severity of myopia grows every year by 5–7%. The increase in morbidity of the eyes and adnexa in the Central Federal District for 2019–2021 was +57.5%, however, morbidity statistics do not consider the age distribution of diseases and their structure. The largest (+296.0 +110.1%) increase per 100 thousand population is observed for the Vladimir, Voronezh, Lipetsk, Ivanovo and Kaluga regions. It was revealed that in 2017, the incidence rate of eyes and their appendages in the Voronezh region over 10 years increased from 64.8 to 94.8 per 1000 students, 45.6% of students had impaired visual acuity. In the region, there is a staff shortage of ophthalmologists, insufficient coverage of preventive examinations and a low level of detection of patients at an early stage of disease. Conclusion. The epidemiology of eye diseases on the territory of the Russian Federation and its constituent entities in the young population has not been sufficiently studied. Improving regional analysis tools will help identify factors of variability in the epidemiology of eye diseases across the country’s regions. In regions with a high increase in ophthalmic morbidity, it is necessary to study in more detail the epidemiology of vision diseases in young people.

Mapping Interindividual Variability of Toxicodynamics Using High-Throughput Transcriptomics and Primary Human Hepatocytes from Fifty Donors.

Understanding the variability across the human population with respect to toxicodynamic responses after exposure to chemicals, such as environmental toxicants or drugs, is essential to define safety factors for risk assessment to protect the entire population. Activation of cellular stress response pathways are early adverse outcome pathway (AOP) key events of chemical-induced toxicity and would elucidate the estimation of population variability of toxicodynamic responses. We aimed to map the variability in cellular stress response activation in a large panel of primary human hepatocyte (PHH) donors to aid in the quantification of toxicodynamic interindividual variability to derive safety uncertainty factors. High-throughput transcriptomics of over 8,000 samples in total was performed covering a panel of 50 individual PHH donors upon 8 to 24 h exposure to broad concentration ranges of four different toxicological relevant stimuli: tunicamycin for the unfolded protein response (UPR), diethyl maleate for the oxidative stress response (OSR), cisplatin for the DNA damage response (DDR), and tumor necrosis factor alpha () for signaling. Using a population mixed-effect framework, the distribution of benchmark concentrations (BMCs) and maximum fold change were modeled to evaluate the influence of PHH donor panel size on the correct estimation of interindividual variability for the various stimuli. Transcriptome mapping allowed the investigation of the interindividual variability in concentration-dependent stress response activation, where the average of BMCs had a maximum difference of 864-, 13-, 13-, and 259-fold between different PHHs for UPR, OSR, DDR, and signaling-related genes, respectively. Population modeling revealed that small PHH panel sizes systematically underestimated the variance and gave low probabilities in estimating the correct human population variance. Estimated toxicodynamic variability factors of stress response activation in PHHs based on this dataset ranged between 1.6 and 6.3. Overall, by combining high-throughput transcriptomics and population modeling, improved understanding of interindividual variability in chemical-induced activation of toxicity relevant stress pathways across the human population using a large panel of plated cryopreserved PHHs was established, thereby contributing toward increasing the confidence of in vitro-based prediction of adverse responses, in particular hepatotoxicity. https://doi.org/10.1289/EHP11891.

Multi-Objective Battery Coordination in Distribution Networks to Simultaneously Minimize CO2 Emissions and Energy Losses

The techno–environmental analysis of distributed energy resources in electrical distribution networks is a complex optimization task due to the non-convexities of its nonlinear programming formulation. This research employs convex optimization to address this issue while minimizing the expected carbon dioxide emissions and daily energy losses of a distribution grid via the optimal dispatch of battery energy storage units (BESUs) and renewable energy units (REUs). The exact non-convex model is approximated via semi-definite programming in the complex variable domain. The optimal Pareto front is constructed using a weighting-based optimization approach. Numerical results using an IEEE 69-bus grid confirm the effectiveness of our proposal when considering unitary and variable power factor operation for the BESUs and the REUs. All numerical simulations were carried out using MATLAB software (version 2022b), a convex disciplined tool (CVX), and the semi-definite programming solvers SEDEUMI and SDPT3.

A Variable Eddington Factor Model for Thermal Radiative Transfer with Closure Based on Data-Driven Shape Function

A new variable Eddington factor (VEF) model is presented for nonlinear problems of thermal radiative transfer (TRT). The VEF model is data-driven and acts on known (a-priori) radiation-diffusion solutions for material temperatures in the TRT problem. A linear auxiliary problem is constructed for the radiative transfer equation (RTE) whose emission source and opacities are evaluated at these known material temperatures. The solution to this RTE approximates the specific intensity distribution in phase-space and time. It is applied as a shape function to define the Eddington tensor for the presented VEF model. The shape function computed via the auxiliary RTE problem will capture some degree of transport effects within the TRT problem. The VEF moment equations closed with this approximate Eddington tensor will thus carry with them these captured transport effects. In this study, the temperature data comes from multigroup P 1 , P 1 / 3 , and flux-limited diffusion radiative transfer models. The proposed VEF model can be interpreted as a transport-corrected diffusion reduced-order model. Numerical results are presented on the Fleck-Cummings test problem which models a supersonic wavefront of radiation. The VEF model is shown to improve accuracy by 1–2 orders of magnitude compared to the considered radiation-diffusion model solutions to the TRT problem.

Interpreted depositional conditions of balanced-fill lake basin strata incorporating vertebrate and invertebrate trace fossils, Triassic Santa Clara sub-basin, Cuyana rift basin, Argentina

ABSTRACT The Santa Clara Abajo and Santa Clara Arriba formations host a diverse assemblage of trace fossils that record a wide range of behaviors and a broad array of ecological niches during the Middle Triassic—a critical period in the evolution of continental fauna with the diversification of both synapsids (cynodont and dicynodont) and archosauromorphs (dinosaurs, pterosaurs, and crocodilians) that represent post-Permian faunal recovery. The Santa Clara formations are part of the continental infill of the Cuyana rift basin in Argentina and represent a lacustrine system with fluvial input and delta development. Sedimentological characteristics of these units as well as their stacking patterns characterize a “fluctuating profundal” facies association typical of a balanced-fill lake basin. The lacustrine and associated terrestrial environments preserve a rich record of invertebrate traces with 26 ichnogenera from ethological classes of fodichnia, domichnia, repichnia, pascichnia, and cubichnia occupying all continental tiers (subaerial and subaqueous, surficial, and/or very shallow, shallow, mid, and deeper) and ecological niches (epiterraphilic, terraphilic, hygrophilic, and hydrophilic). In association with invertebrate traces, two taphonomic modes of tetrapod footprints have been found: a moderate-fidelity mode and a high-fidelity mode. Physical sedimentary features, burrows, trails, and tracks, and their stratigraphic positions are integrated to interpret the main factors involved in footprint preservation in these subsettings. The most significant and variable preservational factor found is water-table fluctuation controlled by the paleohydrology of a balanced-fill lake system. These data show that in balanced-fill lake systems, diverse trace assemblages occur in the lake and associated subsettings such as delta plains and lake-margin settings, whereas trace fossils can be totally absent in coeval lake-center strata, particularly if anoxic lake-bottom conditions occur, as probably occurred in the meromictic Santa Clara lake system.

Painlevé analysis, Painlevé–Bäcklund, multiple regular and singular kink solutions of dynamical thermopherotic equation drafting wrinkle propagation

The thermophoretic motion (TM) system with a variable heat transmission factor, based on the Korteweg-de Vries (KdV) equation, is used to model soliton-like thermophoresis of creases in graphene sheets. Painlevé test is employed to discover that the equation is Painlevé integrable. Then an auto-Bäcklund transformation using the truncated Painlevé expansion is obtained. Concerning the additional variables, the auto-Bäcklund transformations convert the nonlinear model to a set of linear partial differential equations. Finally, various explicit precise solutions based on the acquired auto-Bäcklund transformations are investigated and the researched solutions are illustrated in 3D, 2D and contour plots. Furthermore, the Cole-Hopf transformation is used in conjunction with Hirota’s bilinear technique to get multiple regular and singular kink solutions.

Learning closure relations using differentiable programming: An example in radiation transport

Reduced order models with a-priori unknown closure relations are ubiquitous in transport problems. In this work, we present a machine-learning approach to finding closure relations utilising differentiable programming. We use the Su Olson radiation transport test problem as an example training data set. We present novel closures for second angular moment (variable Eddington factor), third angular moment and flux-limited diffusion models. We evaluate the improvement of the machine-learnt closures over those from the literature. These improvements are then tested by considering a modification to the Su Olson problem. Comparisons to literature closures show the machine learning models out-perform them in both the trained and unseen problems.

Influence of material parameter variability on the predicted coronary artery biomechanical environment via uncertainty quantification.

Central to the clinical adoption of patient-specific modeling strategies is demonstrating that simulation results are reliable and safe. Indeed, simulation frameworks must be robust to uncertainty in model input(s), and levels of confidence should accompany results. In this study, we applied a coupled uncertainty quantification-finite element (FE) framework to understand the impact of uncertainty in vascular material properties on variability in predicted stresses. Univariate probability distributions were fit to material parameters derived from layer-specific mechanical behavior testing of human coronary tissue. Parameters were assumed to be probabilistically independent, allowing for efficient parameter ensemble sampling. In an idealized coronary artery geometry, a forward FE model for each parameter ensemble was created to predict tissue stresses under physiologic loading. An emulator was constructed within the UncertainSCI software using polynomial chaos techniques, and statistics and sensitivities were directly computed. Results demonstrated that material parameter uncertainty propagates to variability in predicted stresses across the vessel wall, with the largest dispersions in stress within the adventitial layer. Variability in stress was most sensitive to uncertainties in the anisotropic component of the strain energy function. Moreover, unary and binary interactions within the adventitial layer were the main contributors to stress variance, and the leading factor in stress variability was uncertainty in the stress-like material parameter that describes the contribution of the embedded fibers to the overall artery stiffness. Results from a patient-specific coronary model confirmed many of these findings. Collectively, these data highlight the impact of material property variation on uncertainty in predicted artery stresses and present a pipeline to explore and characterize forward model uncertainty in computational biomechanics.

Toward Standardized Aerovirology: A Critical Review of Existing Results and Methodologies.

Understanding the airborne survival of viruses is important for public health and epidemiological modeling and potentially to develop mitigation strategies to minimize the transmission of airborne pathogens. Laboratory experiments typically involve investigating the effects of environmental parameters on the viability or infectivity of a target airborne virus. However, conflicting results among studies are common. Herein, the results of 34 aerovirology studies were compared to identify links between environmental and compositional effects on the viability of airborne viruses. While the specific experimental apparatus was not a factor in variability between reported results, it was determined that the experimental procedure was a major factor that contributed to discrepancies in results. The most significant contributor to variability between studies was poorly defined initial viable virus concentration in the aerosol phase, causing many studies to not measure the rapid inactivation, which occurs quickly after particle generation, leading to conflicting results. Consistently, studies that measured their reference airborne viability minutes after aerosolization reported higher viability at subsequent times, which indicates that there is an initial loss of viability which is not captured in these studies. The composition of the particles which carry the viruses was also found to be important in the viability of airborne viruses; however, the mechanisms for this effect are unknown. Temperature was found to be important for aerosol-phase viability, but there is a lack of experiments that directly compare the effects of temperature in the aerosol phase and the bulk phase. There is a need for repeated measurements between different research groups under identical conditions both to assess the degree of variability between studies and also to attempt to better understand already published data. Lack of experimental standardization has hindered the ability to quantify the differences between studies, for which we provide recommendations for future studies. These recommendations are as follows: measuring the reference airborne viability using the "direct method"; use equipment which maximizes time resolution; quantify all losses appropriately; perform, at least, a 5- and 10-min sample, if possible; report clearly the composition of the virus suspension; measure the composition of the gas throughout the experiment. Implementing these recommendations will address the most significant oversights in the existing literature and produce data which can more easily be quantitatively compared.

Disentangling the hydrological and hydraulic controls on streamflow variability in Energy Exascale Earth System Model (E3SM) V2 – a case study in the Pantanal region

Abstract. Streamflow variability plays a crucial role in shaping the dynamics and sustainability of Earth's ecosystems, which can be simulated and projected by a river routing model coupled with a land surface model. However, the simulation of streamflow at large scales is subject to considerable uncertainties, primarily arising from two related processes: runoff generation (hydrological process) and river routing (hydraulic process). While both processes have impacts on streamflow variability, previous studies only calibrated one of the two processes to reduce biases in the simulated streamflow. Calibration focusing only on one process can result in unrealistic parameter values to compensate for the bias resulting from the other process; thus other water-related variables remain poorly simulated. In this study, we performed several experiments with the land and river components of the Energy Exascale Earth System Model (E3SM) over the Pantanal region to disentangle the hydrological and hydraulic controls on streamflow variability in coupled land–river simulations. Our results show that the generation of subsurface runoff is the most important factor for streamflow variability contributed by the runoff generation process, while floodplain storage effect and main-channel roughness have significant impacts on streamflow variability through the river routing process. We further propose a two-step procedure to robustly calibrate the two processes together. The impacts of runoff generation and river routing on streamflow are appropriately addressed with the two-step calibration, which may be adopted by developers of land surface and earth system models to improve the modeling of streamflow.

Understanding hemoglobin contribution to high-dose methotrexate disposition-population pharmacokinetics in pediatric patients with hematological malignancies.

The aim of the present study was to develop a population pharmacokinetic model for methotrexate (MTX) during high-dose treatment (HDMTX) in pediatric patients with acute lymphoblastic leukemia (ALL) and non-Hodgkin's lymphoma (NHL) and to describe the influence of variability factors. The study included 50 patients of both sexes (aged 1-18years) who received 3 or 5g/m2 of HDMTX. A nonlinear mixed effect modeling approach was applied for data analysis. Parameter estimation was performed by first-order conditional estimation method with interaction (FOCEI), whereas stepwise covariate modeling was used to assess variability factors. The final model is a two-compartment model that incorporates the effect of body surface area and the influence of hemoglobin and serum creatinine on MTX clearance (CL). Population pharmacokinetic values for a typical subject were estimated at 5.75 L/h/m2 for clearance (CL), 21.3 L/m2 for volume of the central compartment (V1), 8.2 L/m2 for volume of the peripheral compartment (V2), and 0.087 L/h/m2 for intercompartmental clearance (Q). According to the final model, MTX CL decreases with increasing serum creatinine, whereas a positive effect was captured for hemoglobin. A difference of almost 32% in MTX CL was observed among patients' hemoglobin values reported in the study. The developed population pharmacokinetic model can contribute to the therapy optimization during HDMTX in pediatric patients with ALL and NHL. In addition to renal function and body weight, it describes the influence of hemoglobin on CL, allowing better understanding of its contribution to the disposition of HDMTX.

Cloud-to-Ground Lightning in Cities: Seasonal Variability and Influential Factors

AbstractUrban-induced land use changes have a significant impact on local weather patterns, leading to increased hydro-meteorological hazards in cities. Despite substantial threats posed to humans, understanding atmospheric hazards related to urbanisation, such as thunderstorms, lightning, and convective precipitation, remains unclear. This study aims to analyse seasonal variability of cloud-to-ground (CG) lightning in the five large metropolitans in Bangladesh utilising six years (2015–2020) of Global Lightning Detection Network (popularly known as GLD360) data. It also investigates factors influencing CG strokes. The analysis revealed substantial seasonal fluctuations in CG strokes, with a noticeable increase in lightning activity during the pre-monsoon months from upwind to metropolitan areas across the five cities. Both season and location appear to impact the diurnal variability of CG strokes in these urban centres. Bivariate regression analysis indicated that precipitation and particulate matter (PM) significantly influence lightning generation, whilst population density, urban size, and mean surface temperature have negligible effects. A sensitivity test employing a random forest (RF) model underscored the pivotal role of PM in CG strokes in four of the five cities assessed, highlighting the enduring impact of extreme pollution on lightning activity. Despite low causalities from CG lightning, the risk of property damage remains high in urban environments. This study provides valuable insights for shaping public policies in Bangladesh, a globally recognised climate hotspot.

Phantomless Computed Tomography-Based Quantitative Bone Mineral Density Assessment: A Literature Review

The global surge in aging populations has intensified osteoporosis challenges, necessitating improved diagnostic methods. While dual X-ray absorptiometry (DXA) is the conventional standard in assessing bone mineral density (BMD), the exploration of quantitative computed tomography (QCT) has been proposed, particularly phantomless techniques. Challenges in single-energy CT, emphasizing internal calibration standards like subcutaneous fat, are discussed. Advances in PL-QCT, notably with automatic region of interest (ROI) selection, show improved accuracy. Dual-energy CT (DECT) introduces new dimensions for musculoskeletal analysis. Despite advancements, challenges persist, including interindividual variability and patient-specific factors. Evolving single-energy CT and DECT techniques show promise in refining BMD assessment and osteoporosis diagnosis, enhancing patient care. Continued research and integration into clinical practice are vital for realizing these advancements’ full benefits. In this review, we evaluate and summarize current evidence on the feasibility and different approaches to achieve analysis of BMD with phantomless QCT.

Lumacaftor/Ivacaftor Population Pharmacokinetics in Pediatric Patients with Cystic Fibrosis: A First Step Toward Personalized Therapy.

A major breakthrough in cystic fibrosis (CF) therapy was achievedAQ1 with CFTR modulators. The lumacaftor/ivacaftor combination is indicated for the treatment of CF in pediatric patients above 6 years old. Pharmacokinetic (PK) studies of lumacaftor/ivacaftor in these vulnerable pediatric populations are AQ2crucial to optimize treatment protocols. The objectives of this study were to describe the population PK (PPK) of lumacaftor and ivacaftor in children with CF, and to identify factors associated with interindividual variability. The association between drug exposure and clinical response was also investigated. A total of 75 children were included in this PPK study, with 191 concentrations available for each compound and known metabolites (lumacaftor, ivacaftor, ivacaftor-M1, and ivacaftor-M6). PPK analysis was performed using Monolix software. A large interindividual variability was observed. The main sources of interpatient variability identified were patient bodyweight and hepatic function (aspartate aminotransferase). Forced expiratory volume in the first second (FEV1) was statistically associated with the level of exposure to ivacaftor after 48 weeks of treatment. This study is the first analysis of lumacaftor/ivacaftor PPK in children with CF. These data suggest that dose adjustment is required after identifying variability factors to optimize efficacy. The use of therapeutic drug monitoring as a basis for dose adjustment in children with CF may be useful.

SOLUBLE CD150 ISOFORM LEVEL IN PLASMA OF CHRONIC LYMPHOCYTIC LEUKEMIA PATIENTS.

SLAMF1/CD150 is an active player in B cell signaling networks in chronic lymphocytic leukemia (CLL). CD150-mediated signaling initiates through a homophilic CD150 binding, which spans the adjacent cells, or the interaction with the soluble CD150 isoform (sCD150). The expression of sCD150 isoform at the mRNA and protein levels ex vivo was confirmed. However, it is unclear whether sCD150 isoform present in the blood plasma of CLL patients is a factor in the constitutive activation of CD150+ cells. The aim of this study was to develop an ELISA assay for the specific sCD150 evaluation and assess the sCD150 levels in the blood plasma of CLL patients with different CD150 expression on B cells. Blood plasma samples and peripheral blood mononuclear cells from 40 previously untreated CLL patients were analyzed. An ELISA method, ex vivo drug sensitivity assay, and a cell viability assay were used. The sCD150 isoform was found in all studied plasma samples of CLL patients at different levels regardless of the cell surface CD150 expression status of B cells and sCD150 mRNA expression. CLL cases with low levels of the cell surface CD150 expression in B cells are characterized by high levels of sCD150 in blood plasma in contrast to the CLL cases with high cell surface CD150 expression on B cells. The elevated levels of sCD150 in blood plasma are associated with a better sensitivity of malignant B cells to cyclophosphamide and bendamustine. The sCD150 isoform is actively secreted by CLL B cells with its accumulation in blood plasma, which may be regarded as an additional factor in the CLL clinicopathologic variability.