Modeling Studies Research Articles

Bayesian age-period-cohort projection of cancers in Iran: a modeling study

IntroductionCancer is a significant public health issue in Iran, and its incidence has been on the rise in recent years. The objective of this study is to predict the incidence of total cancer in Iran using a Bayesian age-period-cohort (APC) model.MethodsUtilizing age-period-cohort modeling, this study assessed the multifaceted effects of age, period, and cohort on cancer incidence during the period spanning 2005 to 2017. Key metrics, including the net drift (representing the overall annual percentage change), local drift (indicating annual percentage changes within specific age groups), and longitudinal age curves (depicting expected age-specific rates over time), were computed. Moreover, the evaluation encompassed an analysis of period and cohort relative risks. To project the future age-standardized incidence rates of cancers from 2018 to 2027, Bayesian age-period-cohort analysis integrated nested Laplace approximations.ResultThe age-standardized incidence rate and the absolute number of cancer cases in Iran showed an upward trend. The net drift was 1.79% (95% confidence interval, CI: 0.87% to 2.72%) for males and 3.31% (95% CI: 2.49% to 4.14%) for females. Local drifts remained consistently above zero for all age groups from 2005 to 2017, except for the under-5 age group in both males and females, and the 45–49 and 50–54 age groups in females. After accounting for period deviations, the risk of cancer incidence exhibited an exponential increase with age for both sexes. Based on the Bayesian age-period-cohort analysis, it is estimated that there will be around 210,701 new cancer cases in 2027. Moreover, the Age-Standardized Rate (ASR) for cancer is anticipated to reach 240.32 per 100,000 by 2027. The forecasts indicate a rise in cancer incidence rates across all age groups for both males and females.ConclusionThis study underscores the urgency of implementing targeted preventive strategies aligned with demographic shifts and lifestyle factors. Emphasizing the role of robust cancer registries, it advocates for continuous monitoring to inform evidence-based interventions.

Genetic inhibition of nicotinamide N-methyltransferase and prevention of alcohol-associated fatty liver in humans.

Recent studies of animal models reported Nicotinamide N-methyltransferase (NNMT) as a potential therapeutic target for preventing alcohol-associated fatty liver (AFL), yet its efficacy and safety in humans remain unknown. We aim to estimate the effectiveness and safety of inhibiting NNMT in humans. We leveraged Electronic Medical Records (EMRs) data coupled with genetic information to perform a retrospective drug target validation study. We examined longitudinal clinical data from 612 individuals with excessive alcohol consumption. Two variants lowering NNMT protein levels were combined to calculate a weighted NNMT genetic score that could mimic mild inhibition of NNMT. Participants with an NNMT score above the median were classified as genetically inhibited, while others were considered non-inhibited. We then evaluated whether genetic inhibition of NNMT would affect the incidence of AFL or the risk of liver injury, to illuminate the effectiveness and safety of genetic inhibition of NNMT respectively. NNMT genetic inhibition correlated with a reduced AFL risk (hazard ratio [HR] 0.67, 95% confidence interval [CI] 0.49-0.90, P = 0.009) without a significant increase in serum aminotransferase levels (P > 0.10). Notably, elevated ALT and AST levels were observed (P < 0.05) in the genetically inhibited group prior to alcohol exposure. These findings suggest NNMT inhibition is a promising avenue for AFL prevention among individuals with excessive alcohol intake. They also underscore the need for precise target population identification to mitigate potential adverse effects.

MacBehaviour: An R package for behavioural experimentation on large language models

The study of large language models (LLMs) and LLM-powered chatbots has gained significant attention in recent years, with researchers treating LLMs as participants in psychological experiments. To facilitate this research, we developed an R package called “MacBehaviour “ (https://github.com/xufengduan/MacBehaviour), which interacts with over 100 LLMs, including OpenAI's GPT family, the Claude family, Gemini, Llama family, and other open-weight models. The package streamlines the processes of LLM behavioural experimentation by providing a comprehensive set of functions for experiment design, stimuli presentation, model behaviour manipulation, and logging responses and token probabilities. With a few lines of code, researchers can seamlessly set up and conduct psychological experiments, making LLM behaviour studies highly accessible. To validate the utility and effectiveness of “MacBehaviour,“ we conducted three experiments on GPT-3.5 Turbo, Llama-2-7b-chat-hf, and Vicuna-1.5-13b, replicating the sound-gender association in LLMs. The results consistently demonstrated that these LLMs exhibit human-like tendencies to infer gender from novel personal names based on their phonology, as previously shown by Cai et al. (2024). In conclusion, “MacBehaviour” is a user-friendly R package that simplifies and standardises the experimental process for machine behaviour studies, offering a valuable tool for researchers in this field.

Informing the decision-making process for potential PMT/vPvM chemicals through the adoption of a risk-based prioritization framework: the ZeroPM approach

A risk-based strategy is presented aimed at prioritizing chemicals screened as potential persistent, mobile and toxic (PMT) or very persistent and very mobile (vPvM) substances. Prioritization is done to strengthen the decision-making process regarding actions that might be taken against chemicals screened as potential PMT/vPvM substances. Such actions can range from acquiring additional data aimed at reducing uncertainties in toxicological effect concentrations or internal exposure concentrations to—in case of acceptable uncertainty—suggesting compounds for prevention and/or removal measures in order to limit future exposure. The prioritization strategy is developed within the ZeroPM project and applies a variety of tools, including in silico and in vitro models for exposure and toxicity hazard assessment. These tools will be applied to chemicals identified as PMT/vPvM substances, with a preliminary emphasis on substances belonging to three chemical classes, i.e. perfluorinated compounds, triazines and triazoles. Here we describe the ZeroPM approach providing a proof-of-principle illustrative example, based on data-rich substances, results from which demonstrate how prioritization can be achieved using a risk-based approach that uses data obtained from new approach methodologies (NAMs) and environmental exposure concentrations, obtained either through modelling or monitoring studies. Results are communicated using a risk-based prioritization matrix, which can be used to help to communicate prioritization needs, such as identifying data gaps or for guiding actions aimed at mitigating exposure. The precision and accuracy of the prioritization matrix is evaluated using several data-rich chemicals, which identifies perfluorooctanoic acid and perfluorooctane sulfonic acid as high priority, due to a combination of toxicity and exposure estimates, whereas atrazine and melamine are observed at lower priority. The proposed risk-based prioritization framework thus represents a complementary source of information that should help support regulatory decision-making for PMT/vPvM substances.

Diurnal temperature variation in surface soils: an underappreciated control on microbial processes

Large diurnal temperature changes (ΔT) (or the diurnal temperature range (DTR)) in surface soils, ranging from 5°C to often greater than 20°C, are generally acknowledged to occur yet largely disregarded in studies that seek to understand how temperature affects microbially-mediated carbon and nitrogen cycling processes. The soil DTR is globally significant at depths of 30 cm or less, occurring from spring through summer in temperate biomes, during summer periods in the arctic, and year-round in the tropics. Thus, although temperature has long been considered an important factor in controlling microbial processes, our understanding of its effects remains incomplete when considering natural soil temperature cycles. Here we show: (1) documented impacts of diurnal temperature changes on microbial respiration rates; (2) documented observations of surface soils with large DTR (&amp;gt;5°C) that affect soil microbial mineralization rates and redox potentials of important biogeochemical reactions; and (3) direct evidence that the constant temperature regime typically used in laboratory soil incubation studies may therefore lead to mischaracterization of in situ temperature controls on microbially influenced processes in the environment. The overall effect is that the DTR yields process rates that are often higher than what has been observed under experimental mean temperature incubation. We suggest that overlooked genetic mechanisms, such as the presence of a circadian clock or thermophilic activity during summer months, are likely contributing to the observed effects of the DTR. To improve our understanding of climate change effects on soil greenhouse gas emissions, nutrient cycling, and other biogeochemical soil processes, we propose a paradigm shift in approach to temperature-inclusive process modeling and laboratory incubation studies that accounts for the important role of natural diurnal temperature fluctuations.

Estimating the incremental population health impact of a multi-cancer early detection (MCED) test to complement existing screening among elevated risk populations with multiple cancer risk factors: a mathematical modeling study

BackgroundThe added benefits of a multi-cancer early detection (MCED) test among individuals with multiple risk factors will help policy decision-makers allocate limited healthcare resources. This study sought to estimate the population health implications of adding an MCED test to standard-of-care (SOC) cancer screening tests among individuals aged 50–79 years with additional cancer risk factors (i.e., tobacco use, family history of cancer, and/or obesity).MethodsA mathematical model was developed to assess the potential screening efficiency of an MCED test in addition to current guideline-recommended screenings. Among the US population of 107 million adults aged 50–79 years, the size of, and cancer risk among specific subgroups (i.e., smokers, obese individuals, those with a family history of cancer) as well as the general population were estimated from the literature. Published estimates of screening uptake and/or performance were used to model the number of cancers detected by SOC screening alone, and the number of incremental cancers that could be detected by an MCED test. Screening efficiency outcomes included the true-positive:false-positive (TP:FP) ratio, diagnostic yield (DY), and cancer detection rate (CDR). Sensitivity analyses were conducted by varying the values of key parameters.ResultsAmong all subgroups, the TP:FP ratios were higher with an MCED test than with SOC screening alone, and higher than in the general population, suggesting improved screening efficiency with an MCED test. The estimated TP:FP ratios were 1:43.3 (SOC)/1:1.1 (MCED), 1:40.4/1:0.8, 1:36.9/1:0.5 among former, ever, and current smokers, respectively, 1:38.3/1:0.9 (those with a family history of cancer), and 1:39.3/1:1.1 (obese individuals). Among the general population, the TP:FP ratios were 1:43.5/1:1.1. Across all subpopulations, the DY and CDR increased by up to threefold with an MCED test, when compared to SOC screening alone, with up to 75% of cancers detected with an MCED test lacking a screening paradigm. These results were robust in sensitivity analyses.ConclusionsAdding an MCED test could improve screening efficiency among individuals with multiple risk factors, as well as the general population.

Effect of changes in skin properties due to diabetes mellitus on the titration period of transdermal fentanyl: single-center retrospective study and diabetic animal model study

BackgroundIn the dose titration of transdermal fentanyl to prevent unrelieved pain, it is important to consider not only dose adjustment, but also the titration period, which is influenced by the time required to reach the steady state. Many patients with cancer pain experience comorbidities that might affect the skin properties and influence transdermal absorption. We hypothesized that skin changes due to diabetes mellitus (DM) would affect the titration period of transdermal fentanyl. We conducted a retrospective study and diabetic animal model study to test this hypothesis.MethodsIn the retrospective study, the titration period was defined in terms of “dose change” and “number of rescue opioids” in patients initiated on transdermal fentanyl. Multiple logistic regression analysis was performed to analyze the relation between the titration period and comorbidities, including DM. In the diabetic animal model study, intercellular lipids of stratum corneum (SC) were analyzed in Goto-Kakizaki (GK) rats, a model of DM, and the pharmacokinetics of intravenously or transdermally administered fentanyl was examined.ResultsIn the retrospective study, the titration period ranged from 5 to 39 days (n = 387), and the patients taking a longer period (6 days or more) was significantly related to in patients with unspecified DM: AOR (95% confidence interval), 0.438 (0.217–0.884). In the diabetic animal model study, the ceramides (CERs) content in the SC was decreased by approximately 30% in GK rats compared to Wistar rats. The absorption rate constant (ka) of fentanyl administered transdermally was increased approximately 1.4-fold in GK rats, though there was no difference in transdermal bioavailability (F) or systemic clearance (CLtot).ConclusionOur results suggest that the steady state of transdermally administered fentanyl is reached sooner in cancer patients with DM as a comorbidity. Earlier pain assessment and dose adjustment may be possible in these patients.

A Two-Center Study of a Prognostic Model Related to Acute Kidney Injury After Allogeneic Hematopoietic Stem Cell Transplantation in Children: Development of a New Predictive Dynamic Nomogram.

The purpose of this study was to develop a straightforward, easy-to-use online dynamic nomogram for the identification of children who are at high risk of developing acute kidney injury (AKI) after allogeneic hematopoietic stem cell transplantation (allo-HSCT). This was a two-center study in which 242 children in Henan Provincial Children's Hospital composed the training cohort, and 115 children in the First Affiliated Hospital of Zhengzhou University composed the validation cohort. Kaplan-Meier survival analysis was used to compare survival between children with nonacute kidney injury (NAKI) and children with AKI. Multivariate logistic regression analysis was used to identify risk factors for AKI in children who underwent HSCT. The selected variables were utilized to construct nomograms, which were validated via the concordance index (C-index), decision curve analysis, calibration curve analysis, and receiver operating characteristic (ROC) curve analysis. Cumulative survival was significantly lower in children with AKI than in children without kidney injury (p<0.01). Eight variables were included in the nomogram: hepatic veno-occlusive disease (HVOD), graft-versus-host disease (GVHD), ferritin, C-reactive protein (CRP), Cytomegalovirus infection (CMV), thrombotic microangiopathy (TMA), human leukocyte antigen (HLA), and nephrotoxic drugs. The nomogram calibration curves in the training and validation cohorts were highly comparable to the standard curves. The areas under the curve (AUCs) of the prediction model were 0.963 and 0.910 in the training cohort and validation cohort, respectively. The decision curve analysis (DCA) revealed that the model had a significant clinical benefit. The occurrence of AKI affects the prognosis of children who undergo HSCT. We developed a dynamic online nomogram for predicting AKI in children who underwent allo-HSCT on the basis of eight variables. The predictive value and clinical benefit of the nomogram model were acceptable.

In Vitro Bioassay and In silico Pharmacokinetic Characteristics of Xanthium strumarium Plant Extract as Possible Acaricidal Agent.

Effective management strategies against tick infestations are necessary because tickborne diseases represent serious hazards to the health of humans and animals worldwide. The aim of this study was to examine the larvicidal and ovicidal properties of Xanthium strumarium extract against a notorious tick species, Rhipicephalus microplus. The maceration method was used to prepare the ethanolic extract of X. strumarium. The extract was then used in an adult immersion test (AIT) and larval packet test (LPT) to asses the plant's toxicity. To elucidate the mode of action, molecular modeling and docking studies were conducted. ADMET analysis was then carried out to find out the drug-likeness profiles of the plant phytochemicals. Significant death rates and egg inhibition were found at different extract doses using the larval packet test (LPT) and adult immersion test (AIT). A concentration-dependent impact was observed at a concentration of 40 mg/mL, which resulted in the maximum larval mortality (92 ± 2.646) and egg inhibition (77.057 ± 2.186). Additionally, the potency of the extract against R. microplus was determined by calculating its fatal concentrations (LC50, LC90, and LC99). A three-dimensional model of the R. microplus octopamine receptor was created, and docking studies showed that the receptor and possible ligands, most notably Xanthatin and Xanthosin, interacted well. The potential of compounds as tick control agents was highlighted by their pharmacokinetic characteristics and toxicity profiles, as revealed by drug-likeness and ADMET studies. Molecular dynamic simulations further demonstrated the stability of the protein-ligand complex, indicating the consistent association between the ligand and the target protein. Overall, this study provides valuable insights into the potential use of X. strumarium extract and its compounds as larvicidal and ovicidal agents against R. microplus, paving the way for further research on tick control strategies.

Glacial isostatic adjustment driven by asymmetric ice sheet melt during the Last Interglacial causes multiple local sea-level peaks

Global mean sea-level (GMSL) change during the Last Interglacial (LIG, 129−116 ka) gives perspective on how ice sheets respond to warming. Observations of multiple peaks in LIG relative sea level (RSL) records, combined with an assumption that the Laurentide Ice Sheet (LIS) collapsed prior to the LIG, have been used to infer Greenland and Antarctic ice sheet melt histories as well as oscillations in LIG GMSL. However, evidence for an LIS outburst flood at ca. 125 ka and extensive early-LIG Antarctic melt suggests that Laurentide remnants may have persisted longer into the LIG than typically thought even as Antarctic melt accelerated. Here, we explore the effect of concurrent early-Holocene Laurentide persistence and Antarctic collapse on glacial isostatic adjustment and sea level. In our models, we hold GMSL constant at present levels (i.e., GMSL = 0) from 128 ka to 117 ka by balancing excess Laurentide ice with early-LIG Antarctic melt. We find that due to glacial isostatic adjustment, this synchronous but asymmetric ice change causes multiple RSL peaks, separated by ∼4.2 ± 2.5 m of RSL fall near North America and ∼1.3 ± 0.7 m around the Indian Ocean. This spatial pattern resembles observations. These results show that multiple peaks in LIG RSL could have occurred with asymmetric ice changes between the Northern and Southern Hemisphere that sum to little, if any, change in GMSL. Our work highlights the need for LIG modeling studies to consider that dynamic cryospheric changes can occur even with near-constant GMSL.

Quantifying the impact of global nitrate aerosol on tropospheric composition fields and its production from lightning NOx

Abstract. Several global modelling studies have explored the effects of lightning-generated nitrogen oxides (LNOx) on gas-phase chemistry and atmospheric radiative transfer, but few have quantified LNOx's impact on aerosol, particularly when nitrate aerosol is included. This study addresses two key questions: (1) how does including nitrate aerosol affect properties such as tropospheric composition, and (2) how do these effects depend on lightning parameterisation and LNOx levels? Using the Met Office's Unified Model–United Kingdom Chemistry and Aerosol (UM–UKCA) global chemistry–climate model, which now includes a modal nitrate aerosol scheme, we investigate these effects with two lightning-flash-rate parameterisations. Our findings show that both nitrate aerosol and LNOx significantly impact tropospheric composition and aerosol responses. Including nitrate aerosol reduces global mean tropospheric OH by 5 %, decreases the tropospheric ozone burden by 4 %–5 %, increases methane lifetime by a similar amount, and alters the top-of-atmosphere (TOA) net downward radiative flux by −0.4 W m−2. The inclusion of nitrate also shifts the aerosol size distribution, particularly in the Aitken and accumulation modes. A 5.2 Tg N yr−1 increase in LNOx from a zero baseline results in global aerosol increases of 2.8 % in NH4, 4.7 % in fine NO3, 12 % in coarse NO3, and 5.8 % in SO4 mass burdens. This much LNOx increase causes relatively small positive changes in aerosol optical depth, TOA radiative flux, and cloud droplet number concentration compared to when nitrate is included. The results, based on a fast uptake rate for HNO3 to produce NH4NO3, likely represent an upper limit on nitrate effects.

The mediating role of nurses' spiritual well-being between moral resilience and compassion fatigue: A multicenter structural equation model study.

To investigate the mediating role of spiritual well-being in the association between compassion fatigue and moral resilience among nurses. Nurses are inevitably placed in situations of compassion fatigue. Their moral resilience and spiritual well-being may play a crucial role in mitigating the impacts of compassion fatigue. Nonetheless, spiritual well-being, which mediates the influence between compassion fatigue and moral resilience, remains scarce among nurses. Cross-sectional and correlational design. Nurses (n=465) from four government-owned tertiary hospitals in Saudi Arabia were recruited and completed three self-report scales from July to December 2023. Descriptive statistics (e.g., mean, standard deviation, frequency, and proportions) and inferential statistics (Spearman rho and structural equation modeling) were used for data analysis. The emerging model afforded acceptable model fit parameters. Moral resilience had a negative effect on compassion fatigue (β=-0.05, p=0.003) and a positive influence on spiritual well-being (β=0.51, p=0.003). Spiritual well-being negatively influenced compassion fatigue (β=-0.90, p=0.003). Moral resilience had a moderate, negative, indirect effect on compassion fatigue through the mediation of spiritual well-being (β=-0.47, p=0.002). Our study offered a model that validated the mediating role of spiritual well-being in the association between moral resilience and compassion fatigue. Moral resilience directly and indirectly influences spiritual well-being and compassion fatigue, respectively. Healthcare institutions that employ nurses must continually assess compassion fatigue levels and provide necessary interventions. Nurses, nurse managers, and healthcare institutions may leverage moral resilience to improve nurses' spiritual well-being while averting the negative effects of compassion fatigue. Healthcare institutions may incorporate spiritual care into their mainstream support interventions to enhance their compassion, reduce fatigue, and enhance their mental well-being.

Development of a human tyrosinase activity inhibition assay using human melanoma cell lysate.

Tyrosinase (TYR) inhibitors are required to treat skin hyperpigmentation. Currently live cell-based TYR assays and mushroom TYR in vitro assays are the common methods used to screen for TYR inhibitors. However, these methods are either time consuming and expensive or are not human TYR (hsTYR) specific. Here, we describe a simple hsTYR assay using cell lysate prepared from pigmented human melanoma cell lines that takes less than 3 hours to complete after collecting cell pellets. We confirmed the assay is species specific by using a known hsTYR inhibitor, kojic acid, as a positive control, while arbutin, which inhibits mushroom TYR, but not hsTYR, was not effective. This assay is a simple method to confirm hsTYR inhibition before conducting follow-up studies in live biological models.

Systems analysis of the national performance management system for TVET lecturers in South Africa

A quality performance appraisal (PA) and continuing professional development (CPD) system is an essential component of a national performance management system for TVET lecturers. It is intended to support an improvement in lecturer quality and accountability, strengthens student graduation rates and feeds national human resource development for sustainable employment. The aim of this research study was to contribute to improvements in the functional integration and synergies between PA and the CPD system as applied in TVET colleges. The study involved the collection of qualitative data at six South African TVET colleges in order to develop a general description that captures the key features and interactions commonly shared across the case studies in a general analytic model. Data collection, coding and analysis informed the iterative development of a systems model based on causal loop analysis (CLA). This application of the CLA tool provided the means to represent multiple relationships and the feedback loops between them visually. We found that four main causal loops strongly influence the dynamics of PA and the CPD system. The findings offer an analytic platform for further research towards strengthening and reviewing the overall performance management system for TVET lecturers.

Physical Modelling of Cross-Wedge Rolling of Ball Studs

The publication presents and reviews the results of a physical modelling study of the Cross Wedge Rolling process of ball-studs. The ball-studs was formed in a double system from C45 steel at 1050°C, while the physical modelling process was performed on a scale of 1:2.5 using Primo plasticine as the model material, which was formed at 5°C. For the real tests, steel tools were used, while for the model tests the tools were made of ABS plastic. The experimental tests were followed by measurements of the individual stud steps. The geometrical analysis of the specimens showed that the model material allowed the shape of the forging obtained in the rolling process to be accurately modelled. Based on the physical modelling studies of the Cross Wedge Rolling process of ball-studs, it was concluded that the ball-studs rolling process can be modelled using PRI MO plasticine. Based on the analysis of the physical modelling results obtained, it was concluded that physical modelling allows the Cross Wedge Rolling process to be modelled with a high convergence of the results obtained in real and physical tests.

The possible antioxidative effects of ketogenic diet by modifying brain klotho expression: a rat model study

ABSTRACT Objectives: The ketogenic diet (KD) has long been used as an alternative nonpharmacological therapy to manage pharmacoresistant epilepsy. The anticonvulsant mechanisms of KD have yet to be fully elucidated. The present study explored whether a KD could exert antioxidative effects by altering brain Klotho (Kl) gene expression. Methods: Thirty male rats were divided into three groups: the normal diet (ND) group received standard rat chow; the calorie-restricted diet (CRD) group was maintained at 90% of the calculated energy need; and the KD group received a diet composed of 8% protein, 2% carbohydrates, and 90% fat (per calorie macronutrient). The levels of β-hydroxybutyrate (BHB) in the serum, Kl gene expression in the brain, and Kl protein, malondialdehyde (MDA), and protein carbonyl (PC) levels in the serum and brain were evaluated by standard methods. Results: The serum BHB levels in the KD group were significantly greater than those in the ND and CRD groups (p < 0.001). The Kl expression in the brain was significantly greater in the KD group than in the ND group (p = 0.028). The brain MDA levels in the KD group were significantly lower than those in the ND group (p = 0.006). Elevated BHB was positively correlated with brain Kl expression (r = 0.668, p < 0.001). The brain MDA levels were negatively correlated with brain Kl expression (r = −0.531, p = 0.003) and serum BHB levels (r = 0.472, p = 0.020). Discussion: KD might exert antioxidative effects by increasing BHB and upregulating Kl in the brain. This could be considered a possible anticonvulsant mechanism of KD.

Molecular modeling studies, in vitro antioxidant and antimicrobial assay and BSA affinity of novel benzyl-amine derived scaffolds as CYP51B inhibitors.

New scaffolds derived from benzylamine were prepared, characterized, and tested for their antimicrobial, antioxidant activities and binding interactions with BSA. Structure-activity relationship analysis revealed that compounds incorporating both benzylamine and quinoline or pyridine moieties (specifically 3a and 3d) demonstrated potent antifungal activity, surpassing that of the standard drug Ketoconazole against Penicillium italicum. Molecular docking studies confirmed significant inhibitory activity against the CYP51B enzyme-an essential component of fungal cell walls. In addition, compounds 3h, 3d and 3b displayed promising DPPH radical scavenging activity, indicating its strong potential as an antioxidant source. Thermodynamic parameters of standard antiradical mechanisms confirmed antiradical capacity expressed via formal hydrogen atom transfer (FHT). The results of spectrofluorometric assays and molecular docking studies on the affinity of the tested compounds for the BSA enzyme confirmed that all compounds show significant binding affinity for active site III, with compound 3d demonstrating the highest binding affinity. Key pharmacokinetic parameters were assessed using ADMET analysis, ensuring the viability of these compounds for potential therapeutic applications.

Prooxidant state in anticancer drugs and prospect use of mitochondrial cofactors and anti-inflammatory agents in cancer prevention.

An extensive body of literature has associated cancer with redox imbalance and inflammatory conditions. Thus, several studies and current clinical practice have relied on the use of anticancer drugs known to be associated with prooxidant state. On the other hand, a number of studies have reported on the effects of several antioxidants, anti-inflammatory agents and of mitochondrial cofactors (also termed mitochondrial nutrients, MNs) in counteracting or slowing carcinogenesis, or in controlling cancer growth. In the available literature, a body of evidence points on the roles of anti-inflammatory agents and of individual MNs against carcinogenesis or in controlling cancer cell proliferation, but only a few reports on the combined use of two or the effect of three MNs. These combinations are proposed as potentially successful tools to counteract carcinogenesis in prospective animal model studies or in adjuvant cancer treatment strategies. A "triad" of MNs are suggested to restore redox balance, mitigate side effects of prooxidative anticancer drugs, or aid in cancer prevention and/or adjuvant therapy. By elucidating their mechanistic underpinnings and appraising their clinical efficacy, we aim to contribute with a comprehensive understanding of these therapeutic modalities.

Optimizing Bike Sharing Demand Prediction: A Comparative Study of Multiple Linear Regression and LSTM Models based on Time and Weather Factors

Optimizing Bike Sharing Demand Prediction: A Comparative Study of Multiple Linear Regression and LSTM Models based on Time and Weather Factors

Improvement of the Performance of An Industrial Wringer

Objective: To maximize the machine's availability through periodic monitoring and propose design improvements to prevent future issues. Context: Overview of the recycling process and the role of the wringer in filtering recycled plastic. Problem Statement: Description of mechanical defects affecting the wringer, including imbalance due to bearing and rotor shaft deformation. Theoretical Analysis: Root Cause Identification, Impact of Imbalance, System Modelling and Simulation Experimental Studies and Strategy: - Practical experiments validate the theoretical and numerical findings and enhance the vibration analysis approach.- Effective scheduling of interventions and repairs is based on the machine's condition, ensuring continuous monitoring through vibration analysis devices. Results and Discussion: Explanation of the proposed modification, including the specific angle adjustment, Discussion on how the adjustment would reduce rotational speed and maintain high wringing performance.