Dose optimization of an adjuvanted peptide-based personalized neoantigen melanoma vaccine.

The advancements in next-generation sequencing have made it possible to effectively detect somatic mutations, which has led to the development of personalized neoantigen cancer vaccines that are tailored to the unique variants found in a patient's cancer. These vaccines can provide significant clinical benefit by leveraging the patient's immune response to eliminate malignant cells. However, determining the optimal vaccine dose for each patient is a challenge due to the heterogeneity of tumors. To address this challenge, we formulate a mathematical dose optimization problem based on a previous mathematical model that encompasses the immune response cascade produced by the vaccine in a patient. We propose an optimization approach to identify the optimal personalized vaccine doses, considering a fixed vaccination schedule, while simultaneously minimizing the overall number of tumor and activated T cells. To validate our approach, we perform in silico experiments on six real-world clinical trial patients with advanced melanoma. We compare the results of applying an optimal vaccine dose to those of a suboptimal dose (the dose used in the clinical trial and its deviations). Our simulations reveal that an optimal vaccine regimen of higher initial doses and lower final doses may lead to a reduction in tumor size for certain patients. Our mathematical dose optimization offers a promising approach to determining an optimal vaccine dose for each patient and improving clinical outcomes.

Pathways to professional mental care in the Swiss young adult community: a case-control study.

Treatment success for mental health (MH) problems depends, among others, on the timeliness of help-seeking. Therefore, we studied the effect of symptoms and reasons for help-seeking on the point-of-contact and the most intensive professional treatment in a community sample. Participants were recruited as part of the 'Bern Epidemiological At-Risk' (BEAR) study on 16-40-year-old community persons of the Swiss canton Bern. Of the 2,683 participants, 615 (22.9%) reported at least one instance of help-seeking for MH problems and were selected for the presented analyses. Help-seeking behavior was assessed by a modified version of the 'WHO pathway-to-care questionnaire', from which the outcome 'most intensive MH professional contact' was generated. The effect of symptoms and reasons for help-seeking were analyzed in separate models using path analyses. Most help-seeking persons sought MH professional help (n = 405; 65.9%) with a high number of medical pre-contacts (n = 233; 37.9%). The 'most intensive MH professional contact' was provided after an average of 1.47 contacts. Both models showed negative associations between non-MH professional pre-contacts and the most intensive, likely most adequate MH treatment. In the symptom model, 'substance misuse' and 'central-vegetative problems' increased the general likelihood of MH professional contact. Our findings highlight the importance of the first point-of-contact in pathways to adequate MH care and, when seeking help from non-MH professional, of quick referrals to MH professionals. Awareness campaigns or training of health professionals, such as general practitioners, may support timely contact with MH professionals to improve diagnosis, prognosis, and outcome.

Activation of Nrf2 pathway as a protective mechanism against oxidative stress-induced diseases: Potential of astaxanthin.

Astaxanthin, a red-orange liposoluble carotenoid, has been the centre of considerable attention in recent years for its numerous biological activities, notably its potent antioxidant activity. It is reported that astaxanthin elicits these biological activities via a number of cellular pathways. The Nrf2/Keap1 pathway is a major regulator of the antioxidant defence system of cells; it modulates the expression of a plethora of genes related to redox homeostasis as well as cellular detoxification. The pathway has received lots of attention as a prospective therapeutic target for diseases related to oxidative stress and inflammation. Several reports have shown that the pathway is inducible by many natural compounds. This present work reviews the Nrf2/Keap1 pathway, its regulation and involvement in diseases, provides a brief overview of naturally occurring compounds as activators of the pathway as well as discusses the effect of astaxanthin on the pathway.

From Nose to Lumbar Spinal Cord - Reduced Sperm Numbers Occur by Olfactory Bulbectomy-Related Onuf's Nucleus Degeneration: New Experimental Evidence for Kallmann Syndrome.

INTRODUCTION: Olfaction and its relation to human health is an area of growing interest. Although olfaction disorders have been considered a part of Kallmann syndrome, the role of olfactory dysfunction on spermatogenesis has not been studied yet. We studied if olfactory bulbectomy (OBX) causes dysfunction in spermatogenesis as a result of Onuf's nucleus damage. METHODS: Twenty-eight male rats were divided into three groups: six as the control (G-1; n = 6), six as the only frontal burr hole applied animals SHAM (G-2; n = 6), and 16 as the study group (G-3; n = 16) in which OBX was performed. The animals were followed for 2 months. After the decapitation of the animals, olfactory bulb (OB) volumes (mm3), the neuron density of the Onuf's nucleus (n/mm3), and sperm density (n/mm3) were estimated stereologically and analyzed. RESULTS: OB volumes (mm3), degenerated neuron density of Onuf's nucleus (n/mm3), and sperm numbers of control, SHAM, and study groups were estimated as: 4 ± 0.5; 6 ± 2 and 103.245 ± 10.841 in G-1; 3.5 ± 0.7; 14 ± 4 and 96.891 ± 9.569 in G-2; and 1.3 ± 0.3; 91 ± 17 and 73.561 ± 6.324 in G-3. The statistical results of degenerated neuron density of Onuf's nucleus and sperm numbers between groups are p < 0.005 for G-1/G-2; p < 0.0005 for G-2/G-3; and p < 0.00001 for G-1/G-3. DISCUSSION: This study first time indicates that Onuf's nucleus degeneration secondary to OBX seems to be responsible for reduced sperm numbers.

Influence of mental health literacy on help-seeking behaviour for mental health problems in the Swiss young adult community: a cohort and longitudinal case-control study.

Poor knowledge about mental health disorders and their treatment likely contributes to the large treatment gap reported for mental health problems. Therefore, we studied the association between mental health literacy (MHL) and active help-seeking in a community sample. Participants were recruited from an add-on questionnaire study to the 'Bern Epidemiological At-Risk' (BEAR) study on 16-40-year-old community subjects of the Swiss canton Bern. At baseline, data of N = 1504, and at 3-year follow-up, data of N = 535 were available. Based on an unlabelled case vignette (on depression or schizophrenia), MHL was assessed by the questionnaire of Angermeyer and colleagues. Cross-sectional and longitudinal baseline predictors of help-seeking were analysed using path analyses. Additionally, sensitivity analyses of the prospective model were computed for sex, vignette, and baseline mental health problems/disorders. Cross-sectionally, help-seeking was associated with non-endorsement of biogenetic causal explanations, presence of mental health problems/disorders, help-seeking before baseline, poorer functioning, and lower health satisfaction. The prospective model was similar; yet, help-seeking at follow-up was associated with endorsements of the causal explanation 'biogenetics' and, additionally, 'childhood trauma' but not the presence of baseline mental health problems/disorders. Sensitivity analyses revealed a significant impact on sex, vignette, and mental health problems/disorders. For example, actual functional problems were predictive in males, while health satisfaction was predictive in females. Our findings indicate that future studies on drivers of help-seeking should assess very large community samples with case vignettes on different mental disorders to examine appropriate subgroups and their likely interaction to address group-specific factors in awareness campaigns.

Utilisation of probiotics for disease management in giant freshwater prawn (Macrobrachium rosenbergii): Administration methods, antagonistic effects and immune response.

The giant freshwater prawn (Macrobrachium rosenbergii) is a high-yielding prawn variety well-received worldwide due to its ability to adapt to freshwater culture systems. Macrobrachium rosenbergii is an alternative to shrimp typically obtained from marine and brackish aquaculture systems. However, the use of intensive culture systems can lead to disease outbreaks, particularly in larval and post-larval stages, caused by pathogenic agents such as viruses, bacteria, fungi, yeasts and protozoans. White tail disease (viral), white spot syndrome (viral) and bacterial necrosis are examples of economically significant diseases. Given the increasing antibiotic resistance of disease-causing microorganisms, probiotics have emerged as promising alternatives for disease control. Probiotics are live active microbes that are introduced into a target host in an adequate number or dose to promote its health. In the present paper, we first discuss the diseases that occur in M. rosenbergii production, followed by an in-depth discussion on probiotics. We elaborate on the common methods of probiotics administration and explain the beneficial health effects of probiotics as immunity enhancers. Moreover, we discuss the antagonistic effects of probiotics on pathogenic microorganisms. Altogether, this paper provides a comprehensive overview of disease control in M. rosenbergii aquaculture through the use of probiotics, which could enhance the sustainability of prawn culture.

Mathematical model of a personalized neoantigen cancer vaccine and the human immune system.

Cancer vaccines are an important component of the cancer immunotherapy toolkit enhancing immune response to malignant cells by activating CD4+ and CD8+ T cells. Multiple successful clinical applications of cancer vaccines have shown good safety and efficacy. Despite the notable progress, significant challenges remain in obtaining consistent immune responses across heterogeneous patient populations, as well as various cancers. We present a mechanistic mathematical model describing key interactions of a personalized neoantigen cancer vaccine with an individual patient's immune system. Specifically, the model considers the vaccine concentration of tumor-specific antigen peptides and adjuvant, the patient's major histocompatibility complexes I and II copy numbers, tumor size, T cells, and antigen presenting cells. We parametrized the model using patient-specific data from a clinical study in which individualized cancer vaccines were used to treat six melanoma patients. Model simulations predicted both immune responses, represented by T cell counts, to the vaccine as well as clinical outcome (determined as change of tumor size). This model, although complex, can be used to describe, simulate, and predict the behavior of the human immune system to a personalized cancer vaccine.

Natural antioxidants in diabetes treatment and management: prospects of astaxanthin.

Diabetes remains a major health emergency in our entire world, affecting hundreds of millions of people worldwide. In conjunction with its much-dreaded complications (e.g., nephropathy, neuropathy, retinopathy, cardiovascular diseases, etc.) it substantially reduces the quality of life, increases mortality as well as economic burden among patients. Over the years, oxidative stress and inflammation have been highlighted as key players in the development and progression of diabetes and its associated complications. Much research has been devoted, as such, to the role of antioxidants in diabetes. Astaxanthin is a powerful antioxidant found mostly in marine organisms. Over the past years, several studies have demonstrated that astaxanthin could be useful in the treatment and management of diabetes. It has been shown to protect ß-cells, neurons as well as several organs including the eyes, kidney, liver, etc. against oxidative injuries experienced during diabetes. Furthermore, it improves glucose and lipid metabolism along with cardiovascular health. Its beneficial effects are exerted through multiple actions on cellular functions. Considering these and the fact that foods and natural products with biological and pharmacological activities are of much interest in the 21st-century food and drug industry, astaxanthin has a bright prospect in the management of diabetes and its complications.

Enhancing astaxanthin yield in Phaffia rhodozyma: current trends and potential of phytohormones.

Astaxanthin is an important ketocarotenoid with remarkable biological activities and high economic value. In recent times, natural astaxanthin production by microorganisms has attracted much attention particularly in pharmaceuticals, nutraceuticals, cosmetics, and food and feed industries. Though, currently, productivity is still low and has restricted scale-up application in the commercial market, microbial production of astaxanthin has enormous prospects as it is a greener alternative to the predominating chemical synthesis. Over the years, Phaffia rhodozyma has attracted immense interest particularly in the field of biovalorization and sustainable production of natural nutraceuticals as a promising source of natural astaxanthin since it is able to use agro-food waste as inexpensive nutrient source. Many research works have, thus, been devoted to improving the astaxanthin yield from this yeast. Considering that the yeast was first isolated from tree exudates, the use of phytohormones and plant growth stimulators as prospective stimulants of astaxanthin production in the yeast is promising. Besides, it has been shown in several studies that phytohormones could improve cell growth and astaxanthin production of algae. Nevertheless, this option is less explored for P. rhodozyma. The few studies that have examined the effect of phytohormones on the yeast and its astaxanthin productivity reported positive results, with phytohormones such as 6-benzylaminopurin and gibberellic acid resulting in increased expression of carotenogenesis genes. Although the evidence available is scanty, the results are promising. KEY POINTS: • Phaffia rhodozyma is a promising source of natural astaxanthin • For industrialization, astaxanthin productivity of P. rhodozyma still needs optimization • Phytohormones could potentially augment astaxanthin yield of P. rhodozyma.

An Update of Lectins from Marine Organisms: Characterization, Extraction Methodology, and Potential Biofunctional Applications.

Lectins are a unique group of nonimmune carbohydrate-binding proteins or glycoproteins that exhibit specific and reversible carbohydrate-binding activity in a non-catalytic manner. Lectins have diverse sources and are classified according to their origins, such as plant lectins, animal lectins, and fish lectins. Marine organisms including fish, crustaceans, and mollusks produce a myriad of lectins, including rhamnose binding lectins (RBL), fucose-binding lectins (FTL), mannose-binding lectin, galectins, galactose binding lectins, and C-type lectins. The widely used method of extracting lectins from marine samples is a simple two-step process employing a polar salt solution and purification by column chromatography. Lectins exert several immunomodulatory functions, including pathogen recognition, inflammatory reactions, participating in various hemocyte functions (e.g., agglutination), phagocytic reactions, among others. Lectins can also control cell proliferation, protein folding, RNA splicing, and trafficking of molecules. Due to their reported biological and pharmaceutical activities, lectins have attracted the attention of scientists and industries (i.e., food, biomedical, and pharmaceutical industries). Therefore, this review aims to update current information on lectins from marine organisms, their characterization, extraction, and biofunctionalities.

HIV/SARS-CoV-2 coinfection: A global perspective.

Since its first appearance in Wuhan, China, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread throughout the world and has become a global pandemic. Several medical comorbidities have been identified as risk factors for coronavirus disease 2019 (COVID-19). However, it remains unclear whether people living with human immunodefeciency virus (PLWH) are at an increased risk of COVID-19 and severe disease manifestation, with controversial suggestion that HIV-infected individuals could be protected from severe COVID-19 by means of antiretroviral therapy or HIV-related immunosuppression. Several cases of coinfection with HIV and SARS-CoV-2 have been reported from different parts of the globe. This review seeks to provide a holistic overview of SARS-CoV-2 infection in PLWH.

NERDSS: A Nonequilibrium Simulator for Multibody Self-Assembly at the Cellular Scale.

Currently, a significant barrier to building predictive models of cellular self-assembly processes is that molecular models cannot capture minutes-long dynamics that couple distinct components with active processes, whereas reaction-diffusion models cannot capture structures of molecular assembly. Here, we introduce the nonequilibrium reaction-diffusion self-assembly simulator (NERDSS), which addresses this spatiotemporal resolution gap. NERDSS integrates efficient reaction-diffusion algorithms into generalized software that operates on user-defined molecules through diffusion, binding and orientation, unbinding, chemical transformations, and spatial localization. By connecting the fast processes of binding with the slow timescales of large-scale assembly, NERDSS integrates molecular resolution with reversible formation of ordered, multisubunit complexes. NERDSS encodes models using rule-based formatting languages to facilitate model portability, usability, and reproducibility. Applying NERDSS to steps in clathrin-mediated endocytosis, we design multicomponent systems that can form lattices in solution or on the membrane, and we predict how stochastic but localized dephosphorylation of membrane lipids can drive lattice disassembly. The NERDSS simulations reveal the spatial constraints on lattice growth and the role of membrane localization and cooperativity in nucleating assembly. By modeling viral lattice assembly and recapitulating oscillations in protein expression levels for a circadian clock model, we illustrate the adaptability of NERDSS. NERDSS simulates user-defined assembly models that were previously inaccessible to existing software tools, with broad applications to predicting self-assembly in vivo and designing high-yield assemblies in vitro.

Predictive model for Zika virus RNA minipool nucleic acid testing in outbreak scenarios.

BACKGROUND: Zika virus (ZIKV), a mosquito-borne flavivirus, causes asymptomatic infections in blood donors and can be transmitted by transfusion. During the 2016 US outbreak, universal individual-donation nucleic acid testing (ID-NAT) was used to screen the blood supply for ZIKV. Testing pooled samples from multiple donations with minipool (MP)-NAT is less sensitive than ID-NAT, which raised questions about its utility in ZIKV outbreaks. STUDY DESIGN AND METHODS: A mathematical model and computer simulation determined the risk of missing ID-NAT-reactive and immunoglobulin (Ig) M-negative donations in a ZIKV outbreak if MP-NAT is used initially instead of ID-NAT. The model calculated the time required for ZIKV RNA to replicate to a concentration detectable by testing donations individually or in pools of 6 (MP6) or 16 (MP16). A computer simulation then randomly selected infection times to determine the probability of detection by the candidate tests. RESULTS: The probability of detecting the first ID-NAT-reactive unit in an outbreak is 92% (2.5th-97.5th percentile, 79%-99%) by MP6 and 85% (2.5th-97.5th percentile, 67%-99%) by MP16. When one donation is detected by MP-NAT, the model predicts that the chance of having missed one or more ID-NAT-reactive donations is 8% to 15%. The probability of missing a unit by MP-NAT is constant over the course of the outbreak (8% by MP6, 15% by MP16). CONCLUSION: The model predicts that the probability that a candidate MP-NAT will detect the first ID-NAT-reactive unit in a ZIKV outbreak is 85% to 92% and remains constant over time.

Cytosolic proteins can exploit membrane localization to trigger functional assembly.

Cell division, endocytosis, and viral budding would not function without the localization and assembly of protein complexes on membranes. What is poorly appreciated, however, is that by localizing to membranes, proteins search in a reduced space that effectively drives up concentration. Here we derive an accurate and practical analytical theory to quantify the significance of this dimensionality reduction in regulating protein assembly on membranes. We define a simple metric, an effective equilibrium constant, that allows for quantitative comparison of protein-protein interactions with and without membrane present. To test the importance of membrane localization for driving protein assembly, we collected the protein-protein and protein-lipid affinities, protein and lipid concentrations, and volume-to-surface-area ratios for 46 interactions between 37 membrane-targeting proteins in human and yeast cells. We find that many of the protein-protein interactions between pairs of proteins involved in clathrin-mediated endocytosis in human and yeast cells can experience enormous increases in effective protein-protein affinity (10-1000 fold) due to membrane localization. Localization of binding partners thus triggers robust protein complexation, suggesting that it can play an important role in controlling the timing of endocytic protein coat formation. Our analysis shows that several other proteins involved in membrane remodeling at various organelles have similar potential to exploit localization. The theory highlights the master role of phosphoinositide lipid concentration, the volume-to-surface-area ratio, and the ratio of 3D to 2D equilibrium constants in triggering (or preventing) constitutive assembly on membranes. Our simple model provides a novel quantitative framework for interpreting or designing in vitro experiments of protein complexation influenced by membrane binding.

An implicit lipid model for efficient reaction-diffusion simulations of protein binding to surfaces of arbitrary topology.

Localization of proteins to a membrane is an essential step in a broad range of biological processes such as signaling, virion formation, and clathrin-mediated endocytosis. The strength and specificity of proteins binding to a membrane depend on the lipid composition. Single-particle reaction-diffusion methods offer a powerful tool for capturing lipid-specific binding to membrane surfaces by treating lipids explicitly as individual diffusible binding sites. However, modeling lipid particle populations is expensive. Here, we present an algorithm for reversible binding of proteins to continuum surfaces with implicit lipids, providing dramatic speed-ups to many body simulations. Our algorithm can be readily integrated into most reaction-diffusion software packages. We characterize changes to kinetics that emerge from explicit vs implicit lipids as well as surface adsorption models, showing excellent agreement between our method and the full explicit lipid model. Compared to models of surface adsorption, which couple together binding affinity and lipid concentration, our implicit lipid model decouples them to provide more flexibility for controlling surface binding properties and lipid inhomogeneity, thus reproducing binding kinetics and equilibria. Crucially, we demonstrate our method's application to membranes of arbitrary curvature and topology, modeled via a subdivision limit surface, again showing excellent agreement with explicit lipid simulations. Unlike adsorption models, our method retains the ability to bind lipids after proteins are localized to the surface (through, e.g., a protein-protein interaction), which can greatly increase the stability of multiprotein complexes on the surface. Our method will enable efficient cell-scale simulations involving proteins localizing to realistic membrane models, which is a critical step for predictive modeling and quantification of in vitro and in vivo dynamics.

Dosimetric response of fabricated Ge-doped optical fibres in computed tomography RQT beam quality x-ray beams.

Novel germanium (Ge)-doped silica glass fibres tailor-made in Malaysia are fast gaining recognition as potential media for thermoluminescence (TL) dosimetry, with active research ongoing into exploitation of their various beneficial characteristics. Investigation is made herein of the capability of these media for use in diagnostic imaging dosimetry, specifically at the radiation dose levels typically obtained in conduct of Computed Tomography (CT). As a first step within such efforts, there is need to investigate the performance of the fibres using tightly defined spectra, use being made of a Philips constant potential industrial x-ray facility, Model MG165, located at the Malaysian Nuclear Agency Secondary Standards Dosimetry Lab (SSDL). Standard radiation beam qualities (termed RQT) have been established for CT, in accord with IEC 61267: 2003 and IAEA Technical Reports Series No. 457: 2007. A calibrated ionisation chamber has also been utilised, forming a component part of the SSDL equipment. The fabricated fibres used in this study are 2.3 mol% flat fibre (FF) of dimensions 643 × 356 µm2 and 2.3 mol% cylindrical fibre (CF) of 481 µm diameter, while the commercial fibre used is 4 mol% with core diameter of 50 µm. The dopant concentrations are nominal preform values. The fibres have been irradiated to doses of 20, 30 and 40 milligray (mGy) for each of the beam qualities RQT 8, RQT 9 and RQT 10. For x-rays generated at constant potential values from 100 to 150 kV, a discernible energy-dependent response is seen, comparisons being made with that of lithium fluoride (LiF) thermoluminescence dosimeters (TLD-100). TL yield versus dose has also been investigated for x-ray doses from 2 to 40 mGy, all exhibiting linearity. Compared to TLD-100, greater sensitivity is observed for the fibres.

Bone mineral density and insulin-like growth factor-1 in children with spastic cerebral palsy.

BACKGROUND: Children with cerebral palsy (CP) have significant decrease linear growth rate and low bone mineral density (BMD). AIMS: This study is to evaluate BMD in children with CP and its relation to the levels of insulin-like growth factor-1 (IGF-1). SUBJECTS AND METHODS: This cross-sectional study was carried out on 58 children suffering from spastic CP with the age range 4-12 years compared to 19 controls. All assessed by dual energy x-ray absorptiometry (DXA) to measure BMD, serum level of IGF-1, and serum vitamin D. The patients were classified according to their GMFCS. RESULTS: Fractures were reported in seven (12.1%) of cases. Our study demonstrated that, IGF-1 level and BMD decrease in correlation with the severity of CP. IGF-1correlates positively with serum vitamin D, BMI, and BMD. CP children with severe GMFCS level or who use anticonvulsive drugs are at a high risk for low BMD and low levels of IGF-1. CONCLUSION: Both BMD and IGF-1 were significantly in low children with spastic CP; IGF-1 negatively correlates with the severity of osteopenia in children with spastic. Children with CP who are not independently ambulant or with severe GMFCS level or who use anticonvulsive drugs are at a high risk for developing low BMD.

Ursodeoxycholic acid upregulates ERK and Akt in the protection of cardiomyocytes against CoCl2.

Ursodeoxycholic acid (UDCA) is used to treat liver diseases and demonstrates cardioprotective effects. Accumulation of the plasma membrane sphingolipid sphingomyelin in the heart can lead to atherosclerosis and coronary artery disease. Sphingomyelinases (SMases) break down sphingomyelin, producing ceramide, and inhibition of SMases activity can promote cell survival. We hypothesized that UDCA regulates activation of ERK and Akt survival signaling pathways and SMases in protecting cardiac cells against hypoxia. Neonatal cardiomyocytes were isolated from 0- to 2-day-old Sprague Dawley rats, and given 100 µM CoCl2, 150 µM H2O2, or placed in a hypoxia chamber for 24 h. The ameliorative effects of 100-µM UDCA treatment for 12 h were then assessed using MTS, QuantiGene Plex (for Smpd1 and Smpd2), and SMase assays, beating rate assessment, and western blotting (for ERK and Akt). Data were analyzed by the paired Student t-tests and one-way analyses of variance. Cell viability decreased significantly after H2O2 (85%), CoCl2 (50%), and hypoxia chamber (52%) treatments compared to the untreated control (100%). UDCA significantly counteracted the effects of chamber- and CoCl2- induced hypoxia on viability and beating rate. However, no significant differences were observed in acid SMase gene and protein expression between the untreated, CoCl2, and UDCA-CoCl2 groups. In contrast, neutral SMase gene and protein expression did significantly differ between the latter two groups. ERK and Akt phosphorylation was higher in hypoxic cardiomyocytes treated with UDCA than those given CoCl2 alone. In conclusion, UDCA regulates the activation of survival signaling proteins and SMases in neonatal rat cardiomyocytes during hypoxia.

Theory of bi-molecular association dynamics in 2D for accurate model and experimental parameterization of binding rates.

The dynamics of association between diffusing and reacting molecular species are routinely quantified using simple rate-equation kinetics that assume both well-mixed concentrations of species and a single rate constant for parameterizing the binding rate. In two-dimensions (2D), however, even when systems are well-mixed, the assumption of a single characteristic rate constant for describing association is not generally accurate, due to the properties of diffusional searching in dimensions d ≤ 2. Establishing rigorous bounds for discriminating between 2D reactive systems that will be accurately described by rate equations with a single rate constant, and those that will not, is critical for both modeling and experimentally parameterizing binding reactions restricted to surfaces such as cellular membranes. We show here that in regimes of intrinsic reaction rate (ka) and diffusion (D) parameters ka/D > 0.05, a single rate constant cannot be fit to the dynamics of concentrations of associating species independently of the initial conditions. Instead, a more sophisticated multi-parametric description than rate-equations is necessary to robustly characterize bimolecular reactions from experiment. Our quantitative bounds derive from our new analysis of 2D rate-behavior predicted from Smoluchowski theory. Using a recently developed single particle reaction-diffusion algorithm we extend here to 2D, we are able to test and validate the predictions of Smoluchowski theory and several other theories of reversible reaction dynamics in 2D for the first time. Finally, our results also mean that simulations of reactive systems in 2D using rate equations must be undertaken with caution when reactions have ka/D > 0.05, regardless of the simulation volume. We introduce here a simple formula for an adaptive concentration dependent rate constant for these chemical kinetics simulations which improves on existing formulas to better capture non-equilibrium reaction dynamics from dilute to dense systems.