Drug-target residence time (τ) is reviewed from two perspectives: mathematics and molecular dynamics. The first focuses on the quantification of τ using a mathematical formalism applicable to different pharmacological mechanistic conditions. This formalism is based on the concept of the smallest-modulus eigenvalue of a subsystem of interest, in which the global formation process has been eliminated. The second includes relevant studies of recent years to provide a structural explanation of τ predictions. Special attention is paid to physically supported artificial intelligence methods. The main objective of this minireview is to promote a combined approach in which mathematics and physics work synergistically to describe the complexity associated with τ in G protein-coupled receptors.

Mathematical modeling and techno-economic evaluation of building-integrated colored photovoltaics

Quantifying soil micro-element state distribution and predicting tillage performance during sodic saline-alkali subsoiling based on mathematical model and DEM simulation approach

Corneal staining: Beyond the grade.

Exploring synergistic therapeutic potential of Erlotinib and artemisinin in non-small cell lung Cancer (NSCLC) using pharmacological networking and mathematical modeling.

Concerns about the unintended consequences of using pesticides in agricultural settings have led to a shift in practise towards more environmentally friendly methods such as composting, manuring and using plant growth-promoting bacteria. While compost is known for its ability to promote plant growth and serve as a soil amendment, little is known about the various types of bacteria that can be found in it and how effective they are in sustainable agriculture. This study was designed to assess the potency of a few common isolates from local compost by quantifying their capacity to fix nutrients, produce growth hormone, mitigate abiotic stress, produce lignocellulose-degrading enzyme and produce soil-amending enzyme, all while scaling them using an objective in silico method. In addition, the isolates were tested in the field against test crops selected from the monocot and dicot families, namely maize (Zea mays) and okra (Abelmoschus esculentus). When comparing the treated settings to the untreated control setups, an increase was seen in the quantity of fruits (okra) and percentage of grain filling (maize). By creating a score system, an attempt was made to compare the efficiency of five strains based on the invitro and invivo experiments.

Rhetorical evolution in mathematical modelling: A diachronic analysis of metadiscourse in MCM/ICM contest papers

Advancing green lithium-ion battery supply chains: A two-stage framework integrating reinforcement learning and mathematical modeling

Systematic investigation of aflatoxigenic Aspergillus flavus inhibition: Integrating essential oils-based formulation with mathematical modeling and transcriptomic analysis.

Mathematical identification model for transformer oil BLEVE risk under coupled high-temperature and high-pressure conditions

Meticulous determination of the time since death (TSD) is critical in certain criminal investigations. This study aimed to identify optimal markers for TSD estimation and develop a mathematical model applicable under varying conditions. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and β-Actin (ACTB) mRNA levels were analyzed in 10 human skeletal muscle samples using real-time quantitative PCR at eight time intervals (6, 12, 18, 24, 30, 36, 42, and 48 h) within 48 h postmortem at 25°C. Among the candidate markers, GAPDH demonstrated the strongest correlation with times since death. At the same time, ACTB expression remained comparatively stable across all samples and time points as identified by RefFinder (reference gene analysis tool). Mathematical equations were developed using the Ct values for GAPDH, ACTB, and ΔCt (GAPDH-ACTB) and the cubic model gave the highest determination of coefficient while the error rates were low in the quadratic model. The findings indicate that ACTB is an optimal marker for estimating TSD within the 30 to 36-h postmortem interval, while GAPDH is more suitable for the 36 to 48-h period.

Mathematical modeling of unsteady flow and heat transfer in a porous square cavity along with thermal radiation and temperature dependent viscosity

Combination therapy for colorectal cancer with anti-PD-L1 and cancer vaccine: A multiscale mathematical model of tumor-immune interactions.

Stochastic modelling of prostate progenitor architecture.

A computational study of entropy measures and topological indices for Magnesium Nitride using curve fitting techniques.

Trends in mathematical modeling of Lobesia botrana growth and voltinism: A comparative review

Mathematical modeling of nonlinear coupled along- and across-wind aeroelastic responses in tall slender structures with square section

Novel mathematical modeling of IT2 Takagi–Sugeno fuzzy PID controllers with triangular FoUs and their application: A MagLev case study

Heart rate (HR) is a major determinant of cardiac output (CO). During tachycardia, adequate left ventricular (LV) filling becomes important; however, excessive tachycardia reduces CO by shortening filling time. The impact of HR on hemodynamics differs according to the underlying cardiac pathological conditions, making HR management challenging. The atrioventricular (AV) time interaction, which represents the temporal coordination between atrial and ventricular functions for optimal LV filling, is key to effective HR management during tachycardia. This study aimed to elucidate tachycardia-induced hemodynamic deterioration by focusing on AV time interaction. A hybrid approach combining animal experiments and computer simulations was employed. In animal experiments, hemodynamics and mitral valve (MV) flow at HR of 90-180bpm were recorded in eight beagles. The relationship among LV end-diastolic pressure (LVEDP), left atrial pressure (LAP), and changes in MV E-A waves were evaluated. In simulation experiments, hemodynamics at HR of 50-150bpm were analyzed using a cardiovascular mathematical model across five pathological conditions. In animal experiments, CO peaked at HR of 130-140bpm, coinciding with MV E-A wave fusion and a decreased LVEDP/LAP ratio. Simulation studies showed effective tachycardic compensation in systolic and diastolic dysfunction. However, prolonged relaxation time and prolonged AV delay led to decreased CO at high HR. AV time interaction manifests as E-A wave fusion and decreased LVEDP/LAP ratio. Simulation studies suggest that conditions directly affecting filling time significantly impair AV time interaction and lead to circulatory deterioration during tachycardia. These findings highlight the importance of individualized HR management.

Could malaria mosquitoes be controlled by periodic releases of transgenic mosquitocidal Metarhizium pingshaense fungus? A mathematical modeling approach