Logistic Function Research Articles

Reproductive Potential and Population Growth of the Worm Enchytraeus buchholzi (Clitellata: Enchytraeidae) Under Laboratory Conditions as Well as Regression Models

The worm Enchytraeus buchholzi is a new pest injuring American ginseng Panax quinquefolium. To explore its reproductive potential and then estimate its population dynamics, the authors conducted two related experiments: (1) measuring individual fecundity in its lifetime by rearing each of the parent adults alone in a wet sandy dish at 18 and 21 °C indoors; (2) testing population growth by rearing each of the parent adults together with its offspring for a time longer than two generations at 21 °C. In Experiment I, five dependent variables, namely daily mean cocoons (DMC), cumulative cocoons (CC), eggs per cocoon (EPC), daily mean eggs (DME) and cumulative eggs (CE), were extracted, with each of them subject to a stepwise regression analysis on rearing time (T) and its power series as independent variables. Equaling to the net reproductive rate (R0), the generational adult equivalent (GAE) was calculated via a conversion of F1 generational eggs into adult equivalents (AE). In Experiment II, both an exponential and a logistic function were applied to construct regression equations. The results indicated that (1) a parent adult of E. buchholzi was able to live for a period as long as 10 and 13 full generations at the two temperatures tested and lay 84.8 and 110.6 cocoons containing 545 and 714 eggs, respectively; (2) DMC reached its maximum between 7 and 9 days of rearing and then declined slowly along a straight regression line; (3) CC rose steadily along a quadratic curve; (4) both EPC and DME varied following a cubic curve; (5) CE increased steadily along a cubic curve; (6) the new polynomial models suitably reflected the numerical growth trends of cocoons and eggs in the F1 generation in a broad sense, while corresponding derivative equations quantified both the daily reproductive potential and resistance of the worm, thus revealed its daily reproductive capacity; (7) R0 was 41.2 AE at 21 °C and 42.5 AE at 18 °C when a population of E. buchholzi lived in a niche with unlimited ambient resources; (8) this kind of temporal population generated by individual reproduction had fully demonstrated its significant, generational reproductive potential; and (9), through living in such a limited area as the wet sandy dish, bypassing an exponential growth process, the laboratory population grew up along a logistic curve from the F1 to F3 generations. The statistical relationships help to comprehend the individual reproduction of E. buchholzi, understand deeply the logical sequence and the difference between individual and population reproductions, predict population dynamics of the worm, and provide its integrated pest management with a solid basis. The experimental study has expanded theories on bionomics and population ecology, opening up a new area for research work in related fields.

Generalized Logistic Function: A Retracker to Improve the Accuracy of Water Level Time Series in Coastal Areas and Lakes

The efficiency of satellite altimetry in monitoring coastal areas and lakes is limited due to the contaminated waveform caused by non-water features included in the satellite footprint. Therefore, to mitigate these limitations, waveforms need to be retracked. In this research, the Generalized Logistic Function (GLF) has been introduced with Analytical (GLFA) and Numerical (GLFN) approaches to retrack the first sub-waveform. The results have been compared with those obtained from on-board retrackers existing in Level-2 altimetry data, the retracking of the full-waveform, the first sub-waveform, and the mean of the sub-waveforms using the threshold retracker. The Level-2 and Level-1B data of the Sentinel-3A (SRAL) mission for passes 141, 700, 244, and 311, respectively, passing over Vättern and Hjälmaren Lakes in Sweden, and 0–2 km distance from the coasts of the Bay of Alcudia and the Northeast Gulf of Bothnia from January 2019 to December 2022, were investigated. The results of the retracking approaches used in this study were evaluated against tide gauge data in terms of RMSE and its improvement percentage. The results demonstrate the superiority of the GLFA over the GLFN in coastal areas, while over lakes, the results are nearly equivalent. The improvement percentages of RMSE for the GLFA and GLFN compared to on-board retrackers, respectively, are as follows: for Vättern Lake, 53% and 58%; for Hjälmaren Lake, 40% and 33%; for the Bay of Alcudia, 81% and 46%; and for the Northeast Gulf of Bothnia, the GLFA shows a 36% improvement, while the GLFN yields results equivalent to on-board retrackers. The GLF has shown better performance compared to other approaches, except for Vättern Lake, which yields results almost equivalent to the first sub-waveform retracking approach. Additionally, the mean of the sub-waveform retracking approach by making use of the threshold algorithm has mostly demonstrated weaker performance compared to other methods.

Analysis and computations of a stochastic Cahn–Hilliard model for tumor growth with chemotaxis and variable mobility

Abstract In this work, we present and analyze a system of PDEs, which models tumor growth by taking into account chemotaxis, active transport, and random effects. Tumor growth may undergo erratic behaviors such as metastases that cannot be predicted simply using deterministic models. Moreover, random perturbations are evident in models accounting for therapeutic treatment in terms of therapy uncertainty or parameter identification problems. The stochasticity of the system is modeled by Wiener noises that appear in the tumor and nutrient equations. The volume fraction of the tumor is governed by a stochastic phase-field equation of Cahn–Hilliard type, and the mass density of the nutrients is modeled by a stochastic reaction-diffusion equation. We allow a variable mobility function and nonincreasing growth functions, such as logistic and Gompertzian growth. Via approximation and stochastic compactness arguments, we prove the existence of a probabilistic weak solution and, in the case of constant mobilities, the well-posedness of the model in the strong probabilistic sense. Lastly, we propose a numerical approximation based on the Galerkin finite element method in space and the semi-implicit Euler–Maruyama scheme in time. We illustrate the effects of stochastic forcings in tumor growth in several numerical simulations.

Kinetics, thresholds, and a comparison of mechanisms underlying systemic infection by Listeria monocytogenes

Studies on the system-scale pathogenesis of Listeria monocytogenes infection have classically focused on its ability to colonize in the intestines following an exposure event. However, despite this, many of the most dangerous complications arising from L. monocytogenes infection are observed days, weeks, or months after exposure, resulting indirectly from bacteria escaping this intestinal colonization hub and invading other organs. Over time, findings of various individual phenomena observed during systemic infection have accumulated, including a shift away from the principal route of intestinal dissemination, delays in bacterial colonization of the central nervous system, differing bacterial flux rates across organs, and multi-stability of bacterial population levels. To further our quantitative understanding of foodborne bacterial infection dynamics, a compartmental model of systemic infection which synthesizes these findings is proposed. Under parameterization to infection in BALB/c mice, the model is used to show a substantial decrease in bacterial populations resulting from dissemination through the mesenteric lymph nodes, as compared to the portal vein, when controlling for the number of bacteria passing through each route. Due to the compartmental nature of this model, we anticipate that this result may be paralleled in other microbes which make use of these pathways to escape the intestinal environment. Additionally, we predict thresholds for intestinal dissemination along each of these routes which must be surpassed to induce systemic infection and describe how these thresholds change over time. Supplementarily, logistic curves are fitted to synthetic data as a means of robustly quantifying the dose–response relationship beyond the intestinal barrier.

Dynamics analysis of a reaction-diffusion-advection benthic-drift model with logistic growth.

This paper aims to investigate the benthic-drift population model in both open and closed advective environments, focusing on the logistic growth of benthic populations. We obtain the threshold dynamics using the monotone iteration method, and show that the zero solution is globally attractive straightforward when linearly stable. When unstable, limits from monotonic iteration of upper and lower solutions are upper and lower semi-continuous, respectively. By employing a part metric, we prove these limits are equal and continuous, leading to a positive steady state. In the critical case, we establish that the limit function from the upper solution iteration must be the zero solution by analyzing an algebraic equation. Furthermore, we conduct a quantitative analysis of the principal eigenvalue for a non-self-adjoint eigenvalue problem to examine how the diffusion rate, advection rate, and population release rates influence the dynamics. The results suggest that the diffusion rate and advection rate have distinct effects on population dynamics in open and closed advective environments, depending on the population release rates.

Effects of Ore Particle Size Distribution on Rare Earth Leaching Process of Weathered Crust Elution-Deposited Rare Earth Ores

This paper investigates the rare earth (RE) leaching process of weathered crust leached rare earth ores (WCE-DREOs) with different ore particle sizes. Ore particles were categorized into seven distinct size ranges: −0.106 mm, +0.106 mm to −0.15 mm, +0.15 mm to −0.25 mm, +0.25 mm to −0.85 mm and +0.85 mm. The study examined the correlation between the thickness of the electrical double layer (EDL) and the RE content, as well as the swelling ratio of clay minerals. The findings demonstrated that the order of RE content with respect to varying particle sizes was as follows: C−0.106>C+0.106~−0.15>C+0.15~−0.25>C+0.25~−0.85>C+0.85 (C represents RE content). The RE content of full particle size was found to be 7.93 mg/g, with the particle size −0.106 mm exhibiting the highest RE content of 2.02 mg/g. In the fitting of the relationship between the RE content and the thickness of the EDL, it was observed that the particle size −0.106 mm exhibited a consistent correlation with the Logistic function y=2.03−0.43/(1+1.49x172.39). In the study of the swelling performance of the WCE-DREOs, the order of the swelling ratio of ore samples in different particle sizes was δ−0.106>δ+0.106~−0.15>δ+0.15~−0.25>δ+0.25~−0.85>δ+0.85(δ represents the swelling ratio), and the swelling ratio was 3.34%, 2.92%, 2.33%, 1.55% and 0.01%, respectively. In the fitting of the relationship between the swelling ratio of clay minerals and the thickness of the EDL, it was observed that a particle size of −0.106 mm corresponded to the exponential function y=3.65−99.89·exp⁡−x/0.12. The results of the study provide useful assistance in the mining of the WCE-DREOs.

Climate effect on the seasonal gonad maturity of three commercial penaeid shrimp species in the Gulf of California

Penaeid shrimp represents one of the most economically important fisheries worldwide. In Mexico, they comprise a sequential multispecies fishery with highly variable seasonal and interannual production, presenting its maximum national yield in the Gulf of California (GC) by exploiting the species Litopenaues vannamei, L. stylirostris, and Farfantepenaues californiensis. The yield variability can be related to their reproductive climatic adaptability, measured by the Mexican Fisheries Bureau as the intra and inter-seasonal percentage of mature females (%MF). Currently, shrimp fishery management in Mexico does not explicitly consider the environmental effect within the exploitation strategies for each species, although climatic factors significantly affect this fishery. For this reason, the present study aims to determine a function to estimate the monthly %MF for each commercial penaeid species considering climatic fluctuations. For this objective, the monthly relationship of %MF for each species over 15 years (2001-2015) with the seasonal cycle of the sea surface temperature anomalies (1950-2020) were analyzed and classified by intensity scenarios (normal, warm & cold) in the southern GC, fitting a logistic function based on monthly SST differentials and SST time lags per species. As a result, the model was able to explain 40 to 60% of the %MF variation per species (p<0.001), defining the natural seasonal peaks in the summer and declining towards the winter. Under the climate scenarios, the weak-cold anomalies resulted in the maximum %MF (up to +142% in F. californiensis). Conversely, a minimum %MF (-50%) for the three species resulted from moderate to strong warming anomalies. The %MF of the species with the most tropical affinity (L. vannamei and F. californiensis) were the least vulnerable under weak-warm anomalies, while the more temperate species was the most sensible (L. stylirostris). The model significantly predicted the seasonality of %MF per species and suggests an inverse relationship with SST anomalies, which may have important implications for resource management under climate change and may support the improvement of stock assessment.

Stability and bifurcation analysis of a prey-predator model with Smith growth rate in presence of environmental toxins

The aim of the present article is to formulate a prey-predator model by assuming that the preys inhabit in contaminated environments and undergo Smith growth rate instead of logistic growth rate. Stability and bifurcation phenomenon of the model have been analyzed with utmost care.

A Study of the Population Ecology of Asian Elephants in using the Logistic Growth Model

A Study of the Population Ecology of Asian Elephants in using the Logistic Growth Model

The Effect of Hydrogen Peroxide on Biogas and Methane Produced from Batch Mesophilic Anaerobic Digestion of Spent Coffee Grounds

This paper aims to explore both experimental and modeling anaerobic digestion (AD) processes as innovative methods for managing the substantial quantities of spent coffee grounds (SCG) generated in Algeria, transforming them into valuable renewable energy sources (biogas/methane). AD of SCG, while promising, is hindered by its complex lignocellulosic structure, which poses a significant challenge. This study investigates the efficacy of hydrogen peroxide (H2O2) pretreatment in addressing this issue, with a particular focus on enhancing biogas and methane production. The AD of SCG was conducted over a 46-day period, and the impact of H2O2 pretreatment was evaluated using laboratory-scale batch anaerobic reactors. Four different concentrations of H2O2 (0.5, 1, 2, and 4% H2O2 w/w) were studied in mesophilic conditions (37 ± 2) for 24 h at room temperature, providing basic data on biogas and methane production. The results showed a significant increase in soluble oxygen demand (SCOD) and total sugar solubilization in the range of 555.96–713.02% and 748.48–817.75%, respectively. The optimal pretreatment was found to be 4% H2O2 w/w resulting in 16.28% and 16.93% improvements in biogas and methane yield over the untreated SCG. Further, while previous research has established oxidative pretreatment efficacy, this study uniquely combines the empirical analysis of H2O2 pretreatment with a detailed kinetic modeling approach using the modified Gompertz (MG) and logistic function (LF) models to estimate kinetic parameters and determine the accuracy of fit. The MG model showed the most accurate prediction, thus making the present investigation a contribution to understanding the performance of the AD system under oxidative pretreatment and designing and scaling up new systems with predictability. These findings highlight the potential of H2O2-pretreated SCG as a more efficient and readily available resource for sustainable waste management and renewable energy production.

P-2095. Ultrasensitive Clostridioides difficile Toxin A/B Assay (in Development) for Higher Diagnostic Accuracy

Abstract Background Diagnostic tests for Clostridioides difficile infection (CDI) have either poor sensitivity or specificity, which has led to guideline recommendations for complex multistep testing algorithms. Ultrasensitive C. difficile toxin A/B measurements correlate with disease and may offer a standalone solution for CDI diagnosis. Fluxus develops ultrasensitive, target-agnostic, and low-complexity single-molecule diagnostic instruments based on optofluidic technology that combines integrated optics and microfluidics on a single chip-based system. Here, we report on the preliminary analytical performance of C. difficile toxin A and B assays (in development) powered by the Fluxus technology. Methods C. difficile toxin A (TcdA) and B (TcdB) were spiked into buffer and stool (pooled) and tested across a wide range of TcdA/TcdB concentrations to give dose-response curves and estimate limits of detection (LoD; assay background +2.5 STD of background) and quantification (LoQ; assay background +10 STD of background). TcdA and TcdB concentrations were calculated from a four-parameter logistic nonlinear regression-based calibration curve. Crossreactivity between the toxins was assessed. Further evaluation of expanded analytical and clinical performance is ongoing. Results LoDs in buffer for the prototype TcdA and TcdB assays were 0.47 and 0.98 pg/mL, respectively, and LoQs were 0.91 and 3.34 pg/mL, respectively, with a high dynamic range. LoDs in spiked stool for the TcdA and TcdB assays were 2.02 and 1.15 pg/mL, respectively, and LoQs were 4.25 and 4.35 pg/mL, respectively. There was no crossreactivity between the assay targets across a 4-log dynamic range. Conclusion Fluxus’ ultrasensitive C. difficile toxin A/B assays in development can detect TcdA and TcdB at pg/mL concentrations. Preliminary evaluation of spiked stool samples indicates a comparable dilution linearity to calibrator dose response in buffer. An ultrasensitive C. difficile toxin A/B assay has the potential to provide both high clinical sensitivity and specificity and may replace current testing methods. Disclosures Gipshu Dave, MS, Fluxus, Inc.: Stocks/Bonds (Public Company) Tiffany Truong, MS, Fluxus, Inc.: Stocks/Bonds (Public Company) Mariya Soban, MS, Fluxus, Inc.: Stocks/Bonds (Public Company) Justin Nguyen, BS, Fluxus, Inc.: Stocks/Bonds (Public Company) Frank Zaugg, PhD, Fluxus, Inc.: Stocks/Bonds (Public Company) Valerie Brachet, PhD, Fluxus, Inc.: Stocks/Bonds (Public Company) Peter Wagner, PhD, Fluxus, Inc.: Stocks/Bonds (Public Company) Johanna Sandlund, MD, PhD, Fluxus, Inc.: Stocks/Bonds (Public Company)

Left atrial function is a predictor of 90-day readmissions in patients with a first hospitalization for heart failure

Abstract Aim Heart failure (HF) readmissions are frequent and have important prognostic consequences. LACE index is a tool that estimates the risk of rehospitalization in different clinical scenarios, and has shown moderate discriminatory performance in HF. Our aim was to analyze the association of different clinical and echocardiographic parameters with the risk of 90-day readmissions and to address the performance of the LACE index in our cohort of patients with a first HF hospitalization. Methods Prospective cohort of patients with a first HF hospitalization in a tertiary care center between 2020 and 2022. Clinical, analytical and echocardiographic variables were collected at the time of admission. The primary outcome was 90-day readmissions for HF. Results The mean age of our cohort (n=178) was 73.4 (13) years and 69 (39%) were female. Mean LVEF was 43.8% (15). The prevalence of comorbidities was high: arterial hypertension 71%, diabetes 39%, obesity 29%, atrial fibrillation 25%, and chronic kidney disease 15%. Mean LACE index was 10 (2.8), which corresponds to a high risk of readmission. The incidence of 90-day readmission was 14%. Variables significantly associated with readmission were female sex, history of AF, right ventricular-arterial coupling index, left atrial stiffness, creatinine clearance, and systolic arterial pressure at discharge (Figure 1). A multivariable logistic regression analysis showed that atrial stiffness (OR 1.71; p=0.042) and creatinine clearance (OR 0.95; p=0.066) were the only two independent predictors of readmissions. A model comprising these 2 variables had an area under the ROC curve of 0.758 (95% CI: 0.65-0.84), and was statistically superior to LACE index (AUC 0.55; 95% CI: 0.48-0.63); p&amp;lt;0.005 (Figure 2). Conclusions In a cohort of patients with a first hospitalization for HF and high burden of comorbidities, a simple model which takes into account renal function and left atrial function showed good diagnostic yield for predicting 90-day readmissions. Logistic regression analysis ROC curves

P-1039. Plasma Cathelicidin (LL37) Levels Are not Associated with Candida Gut Colonization in Critically Ill Patients

Abstract Background In the intensive care unit (ICU), Candida spp. gut colonization is a risk factor for Candida bloodstream infection; however, the specific risk factors for Candida gut colonization remain unknown. Impaired anti-microbial immune responses may predispose to Candida gut colonization. LL37, an antimicrobial peptide (AMP) from the cathelicidin family, plays an important role in the immune response to pathogens, including Candida. The purpose of this study was to determine whether plasma LL37 levels are associated with Candida gut colonization in the ICU. Figure 1. Plasma LL-37 levels comparing patients with (Candida=1) and without (Candida=0) Candida gut colonization. Methods We examined a sample of patients enrolled in DYNAMITE (a prospective cohort study of ICU patients at a tertiary care hospital) who provided stool samples. Clinical data was collected by chart review. The first stool sample collected after enrollment was diluted in saline and plated on selective media for Candida spp.; species was identified from positive samples via matrix-assisted laser desorption/time-of-flight. Plasma samples were analyzed for LL37 levels via enzyme-linked immunosorbent assay. LL37 levels were normalized with a four-parameter logistic curve. We compared plasma LL37 levels between patients with and without Candida gut colonization, as well as different colonizing Candida species, using an unpaired t-test in R. Figure 2. Plasma LL-37 levels comparing patients with different Candida species causing gut colonization (0=no Candida gut colonization; 1=C. albicans; 2=C. glabrata; 3=C. parapsilosis; 4=C. albicans/C. glabrata co-colonization). Results Of 31 patients included, 14 (48%) had Candida gut colonization (6 [19%] C. albicans; 5 [16%] C. glabrata; 2 [6%] C. glabrata and C. albicans; 1 [3%] C. parapsilosis). Mean age was 60±16 years; 22 (71%) patients were white; 16 (52%) were women; and 10 (32%) were in shock on ICU admission. There was no statistically significant difference in plasma LL37 between patients with and without Candida gut colonization (mean 44.9± 22.6 ng/mL vs. mean 42.0 ±18.8 ng/mL, respectively, p=0.71) (Figure 1). LL37 levels also did not differ according to colonizing Candida species (Figure 2). Conclusion In this pilot study, plasma LL37 was not found to be associated with Candida gut colonization among ICU patients. These findings suggest that systemic levels may not reflect tissue (intestinal) immune responses. Understanding the role of LL37 and other AMPs in Candida colonization may inspire alternative approaches to reduce Candida colonization and resultant Candida bloodstream infections in the ICU. Disclosures All Authors: No reported disclosures

Investigation of Feeding Effects and Environmental Impact of Fish-Feed Quality: Evidence from Crucian Carp Feeding Experiments

The effects of three types of feed, purchased from online stores and having similar prices, on the growth performance and culture environment of crucian carp (Carassius auratus) were studied in this experiment, which aimed to provide a reference for the evaluation and selection of fish feed. The results showed that feeding different feeds had a significant effect on crucian carp, and that the growth-promoting effect of HD feed (feed produced by Haida Company Limited) was significantly better than that of the other two feeds. For example, the weight gain rate (WGR) of fish in the HD group was 47.1% higher than that in the LD group (p &lt; 0.05), and the WGR of fish in the LD (feed produced by Lianda Company Limited) group was 81.4% higher than that in the TW (feed produced by Tongwei Company Limited) group (p &lt; 0.05). Moreover, the activities of superoxide dismutase and catalase in fish in the HD group was significantly higher than that in the LD and TW groups. Furthermore, we found significant differences in the environmental effects of feeding different feeds. Compared to the LD and HD groups, the environmental impacts for the TW group were more pronounced. The body weight of crucian carp first increased and then stabilized with increasing total dissolved solids (TDS) values. Their quantitative relationship was established based on the von Bertalanffy and Logistic equations (R2 = 0.942–0.995). The results above indicate that, due to differences in feed formulation and the quality of feed raw materials, different feeds have a significant impact on the growth performance and antioxidant indices of fish, as well as on the water environment. Therefore, selecting the appropriate feed is crucial for promoting high-quality development in the aquaculture industry.

Psychopathological Influences on Surgical and Clinical Outcomes in Lumbar Disk Herniation: Prediction Models and Literature Analysis

Background/Objectives: Lumbar disk herniation (LDH) significantly affects quality of life due to lower back and radiating leg pain. Surgical intervention, such as discectomy, is effective for symptom relief when conservative measures fail; however, psychological factors like anxiety, depression, and maladaptive coping strategies may negatively impact surgical outcomes. This study aims to assess the role of preoperative psychological evaluations in predicting postoperative recovery and to identify key psychological and functional predictors of surgical success. Methods: A prospective study was conducted on 888 patients undergoing microdiscectomy for LDH at Mater Olbia Hospital between December 2020 and December 2023. Preoperative evaluations included the Visual Analog Scale, Symptom Checklist 90-R, Oswestry Disability Index, and Short Form 36. Logistic regression models and ROC curve analysis were used to identify significant predictors of outcomes and evaluate model accuracy. Results: Preoperative pain levels and emotional well-being emerged as the strongest determinants of postoperative improvement in the Oswestry Disability Index. The predictive model demonstrated high specificity (90.2%) in identifying patients likely to benefit from surgery. Clinically significant improvements were achieved by 69% of patients, highlighting the importance of psychological and functional assessments. Conclusions: Preoperative psychological assessment is critical in predicting outcomes of lumbar disk herniation surgery. Addressing psychological factors preoperatively enhances recovery, supports personalized treatment planning, and improves patient education. These findings advocate for an integrated care model that considers both physical and psychological health, optimizing surgical outcomes and patient satisfaction.

Prognostic impact of clinical and genetic factors on delayed elimination of methotrexate in children with acute lymphoblastic leukemia

Background. Methotrexate (MTX) in high doses (1000–5000 mg/m2), occupies one of the leading places in modern programs of therapy of acute lymphoblastic leukemia (ALL) in children. Achievement of high long-term survival rates in children with ALL has become possible thanks to this drug. However, no less important problem is the toxicity of the treatment and prediction of its efficacy and safety, in this regard, the role of pharmacogenetic studies in the identification of polymorphisms in candidate genes affecting the pharmacokinetics of MTX is increasing.Objective. To determine predictors of delayed elimination of methotrexate using pharmacokinetic biomarkers in children with acute lymphoblastic leukemia.Materials and methods. We prospectively analyzed the database of pediatric patients with ALL within the framework of an observational (cohort) singlecenter study. The study included 124 children diagnosed with ALL who received therapy according to the ALL-IC BFM 2009 protocol including high-dosed MTX. Real-time PCR method was used to study polymorphisms of ABCB1 and SLCO1B1 genes. The study material was peripheral blood. Statistical analysis ofpharmacogenetic biomarkers influence on toxicity and efficacy of therapy was performed using SPSS Statistics 26.0 program (USA). To form mathematical prognostic models, we used the method of logistic function construction using binary logistic regression with step-by-step selection of factors and, if necessary, additional construction of ROC-curves with subsequent ROC-analysis. Differences were considered significant at p &lt; 0.05; at p ≥ 0.05, differences were considered unlikely and statistically insignificant.Results. Based on the results of the conducted complex analysis of efficacy and safety of high-dosed MTX therapy, a reliable (p &lt; 0.001) prognostic model with high sensitivity, specificity and efficacy (&gt;70 %, respectively) was developed, demonstrating the interrelationships of clinical and genetic factors influencing the delay of MTX elimination in children with ALL, which confirms the necessity of implementing pharmacogenetic testing in real clinical practice.Conclusion. Determination of polymorphisms of genes providing transport and metabolism of cytostatics should be used in practical work of oncohematological clinics for individualization of therapy and ensuring its safety.

Review of the Simulators Used in Pharmacology Education and Statistical Models When Creating the Simulators

Animal experiments have long been used as an educational tool in pharmacological education; however, from the perspective of animal welfare, it is necessary to decrease the number of animals used. ingAlthough using of simulators is effective, the development of these simulators is necessary when there is no existing simulator for animal experiments. In this review, we describe free, downloadable, and commercial simulators that are currently used in pharmacological education. Furthermore, we introduce two strategies to create simulators of animal experiments: (1) bioassay, and (2) experiments that measure the reaction time. We also describe five sigmoid curves (logistic curve, cumulative distribution function [CDF] of normal distribution, Gompertz curve, von Bertalanffy curve, and CDF of Weibull curve) to fit the results and their inverse functions. Using this strategy, it is possible to create a simulator that calculates the reaction time following drug administration. Moreover, we introduce a statistical model for local anesthetic agents using hierarchical Bayesian modeling. Considering the correlation among estimated parameters, we suggest it is possible to create simulators that give results more similar to those of animal experiments. The pharmacological education will be possible by these simulators at educational institutions where animal experiments are difficult due to various restrictions. It is expected that the number of simulator-based education programs will increase in the future.

Quantifying the Effects of Carbon Growth Grade and Structural Diversity on Carbon Sinks of Natural Coniferous–Broadleaved Mixed Forests Across the Jilin Province of China

Natural mixed forests’ carbon sequestration capacity is crucial for mitigating climate change and maintaining ecological balance. However, most of the current studies only consider the role of forest age, ignoring the influence of carbon growth grade and stand structural diversity, which leads to an increase in uncertainty in large-scale forest carbon sink assessment. The aim of this study was to quantify the effects of carbon growth grade and stand structure diversity on the carbon sink of natural mixed forests and to establish a more accurate stand carbon growth model. Based on sample data from the National Forest Inventory (NFI) of China, the stand carbon growth model was established based on Gompertz and Logistic theoretical growth models, and the forest carbon sink at the regional scale was predicted. It was found that the stand carbon growth model considering only the stand age as a single variable often had poor results, with R2 less than 0.36, while R2 values of the optimal model introducing carbon growth grade and stand structural diversity were 0.87 and 0.48, respectively, which significantly improved the prediction accuracy of the model, and both had significant effects on stand carbon stocks. By predicting the future forest carbon sink, it was found that the forest carbon sink of the natural coniferous–broadleaved mixed forests in Jilin Province would reach 791 (781–801) t c/a and 843 (833–852) t c/a in 2030 and 2060, respectively, which were 17% lower and 51% higher than that of the forest carbon sink estimated by considering only the age. Moreover, the model considering structural diversity predicted a more positive carbon sink trend, indicating that forest carbon stocks could be more effectively maintained and carbon sinks increased by increasing the complexity of stand diameter at breast height structure, which has important guiding significance for future forest carbon sink management. This study provides scientific support for achieving the goal of “carbon neutrality” proposed by China.

Comparing Summed Probability Distributions of Shoreline and Radiocarbon Dates from the Mesolithic Skagerrak Coast of Norway

By developing a new methodology for handling and assessing a large number of shoreline dated sites, this paper compares the summed probability distribution of radiocarbon dates and shoreline dates along the Skagerrak coast of south-eastern Norway. Both measures have previously been compared to elucidate demographic developments in Fennoscandia, but these have not been based on probabilistic methods for shoreline dating. The findings indicate a largely diverging development of the two data sets through the Mesolithic. The number of shoreline dated sites undergoes some process of overall decrease through the period, while the radiocarbon data is characterised by a lacking signal in the earliest parts of the period and then undergoes a logistic growth that quickly plateaus and remains stable for the remainder of the period. The precise nature of this discrepancy will necessitate further substantiation and the method of shoreline dating itself still requires further testing and assessment. Having noted this, we still tentatively suggest that while the number of shoreline dated sites is not devoid of influence from a demographic signal, this measure could be more heavily influenced by mobility patterns. Conversely, we also suggest that the lacking radiocarbon data from the earliest part of the Mesolithic is in part the result of mobility patterns, but that the radiocarbon data could be reflecting population dynamics more directly.

Reassessing the Role of Morning Cortisol in Adrenal Insufficiency Diagnosis: Insights from a Multicentric Cohort.

The diagnosis of adrenal insufficiency (AI) is challenging due to nonspecific symptoms. Measuring 8 AM serum cortisol levels is a common screening test, but its accuracy in predicting AI remains uncertain. This study aimed to evaluate the predictive diagnostic value of basal morning cortisol levels in suspected AI cases and compare them with levels in healthy individuals. We have conducted a retrospective multicentric cohort study. The study included an epidemiological cohort (patients with AI suspicion) and a control cohort (healthy volunteers). In the epidemiological cohort an ACTH-stimulation test was performed to confirm (AI group) or exclude (non-AI group) the disease. We have included 273 individuals (168 suspected AI cases and 105 controls). Basal cortisol levels were higher in the control group compared to the AI-suspected group (9.9±3.2 μg/dl vs. 7.7±3.3 μg/dl, p<0.001), though both were below the 15 μg/dl recommended threshold for excluding AI. Within the epidemiological cohort, even after a propensity score matching, taking into consideration sex, age and AI symptoms complaints, no significant difference in basal cortisol levels was found between patients with and without AI [6.10 (4.43; 8.45) vs. 7.14 (4.68; 12.15), p=0.128]. Logistic regression and ROC curve analyses showed a low predictive value for basal cortisol, with a positive predictive value of 18.9% and low specificity. AI patients more frequently experienced hypotension and nausea, compared with non-AI patients. Morning cortisol levels alone are unreliable for diagnosing AI. Revising cortisol cutoffs and incorporating symptom-based criteria may improve diagnostic accuracy.