Growth hormone-releasing hormone agonists ameliorate chronic kidney disease-induced heart failure with preserved ejection fraction.

Therapies for heart failure with preserved ejection fraction (HFpEF) are lacking. Growth hormone-releasing hormone agonists (GHRH-As) have salutary effects in ischemic and nonischemic heart failure animal models. Accordingly, we hypothesized that GHRH-A treatment ameliorates chronic kidney disease (CKD)-induced HFpEF in a large-animal model. Female Yorkshire pigs (n = 16) underwent 5/6 nephrectomy via renal artery embolization and 12 wk later were randomized to receive daily subcutaneous injections of GHRH-A (MR-409; n = 8; 30 µg/kg) or placebo (n = 8) for 4 to 6 wk. Renal and cardiac structure and function were serially assessed postembolization. Animals with 5/6 nephrectomy exhibited CKD (elevated blood urea nitrogen [BUN] and creatinine) and faithfully recapitulated the hemodynamic features of HFpEF. HFpEF was demonstrated at 12 wk by maintenance of ejection fraction associated with increased left ventricular mass, relative wall thickness, end-diastolic pressure (EDP), end-diastolic pressure/end-diastolic volume (EDP/EDV) ratio, and tau, the time constant of isovolumic diastolic relaxation. After 4 to 6 wk of treatment, the GHRH-A group exhibited normalization of EDP (P = 0.03), reduced EDP/EDV ratio (P = 0.018), and a reduction in myocardial pro-brain natriuretic peptide protein abundance. GHRH-A increased cardiomyocyte [Ca2+] transient amplitude (P = 0.009). Improvement of the diastolic function was also evidenced by increased abundance of titin isoforms and their ratio (P = 0.0022). GHRH-A exerted a beneficial effect on diastolic function in a CKD large-animal model as demonstrated by improving hemodynamic, structural, and molecular characteristics of HFpEF. These findings have important therapeutic implications for the HFpEF syndrome.

Controlled Nutrient Delivery to Pancreatic Islets Using Polydopamine-Coated Mesoporous Silica Nanoparticles.

In the present study, we created a nanoscale platform that can deliver nutrients to pancreatic islets in a controlled manner. Our platform consists of a mesoporous silica nanoparticle (MSNP), which can be loaded with glutamine (G: an essential amino acid required for islet survival and function). To control the release of G, MSNPs were coated with a polydopamine (PD) layer. With the optimal parameters (0.5 mg/mL and 0.5 h), MSNPs were coated with a layer of PD, which resulted in a delay of G release from MSNPs over 14 d (57.4 ± 4.7% release). Following syngeneic renal subcapsule islet transplantation in diabetic mice, PDG-MSNPs improved the engraftment of islets (i.e., enhanced revascularization and reduced inflammation) as well as their function, resulting in re-establishment of glycemic control. Collectively, our data show that PDG-MSNPs can support transplanted islets by providing them with a controlled and sustained supply of nutrients.

A Collagen Based Cryogel Bioscaffold that Generates Oxygen for Islet Transplantation.

The aim of this work was to develop, characterize and test a novel 3D bioscaffold matrix which can accommodate pancreatic islets and provide them with a continuous, controlled and steady source of oxygen to prevent hypoxia-induced damage following transplantation. Hence, we made a collagen based cryogel bioscaffold which incorporated calcium peroxide (CPO) into its matrix. The optimal concentration of CPO integrated into bioscaffolds was 0.25wt.% and this generated oxygen at 0.21±0.02mM/day (day 1), 0.19±0.01mM/day (day 6), 0.13±0.03mM/day (day 14), and 0.14±0.02mM/day (day 21). Accordingly, islets seeded into cryogel-CPO bioscaffolds had a significantly higher viability and function compared to islets seeded into cryogel alone bioscaffolds or islets cultured alone on traditional cell culture plates; these findings were supported by data from quantitative computational modelling. When syngeneic islets were transplanted into the epididymal fat pad (EFP) of diabetic mice, our cryogel-0.25wt.%CPO bioscaffold improved islet function with diabetic animals re-establishing glycemic control. Mice transplanted with cryogel-0.25wt.%CPO bioscaffolds showed faster responses to intraperitoneal glucose injections and had a higher level of insulin content in their EFP compared to those transplanted with islets alone (P<0.05). Biodegradability studies predicted that our cryogel-CPO bioscaffolds will have long-lasting biostability for approximately 5 years (biodegradation rate: 16.00±0.65%/year). Long term implantation studies (i.e. 6 months) showed that our cryogel-CPO bioscaffold is biocompatible and integrated into the surrounding fat tissue with minimal adverse tissue reaction; this was further supported by no change in blood parameters (i.e. electrolyte, metabolic, chemistry and liver panels). Our novel oxygen-generating bioscaffold (i.e. cryogel-0.25wt.%CPO) therefore provides a biostable and biocompatible 3D microenvironment for islets which can facilitate islet survival and function at extra-hepatic sites of transplantation.

In vivo imaging of type 1 diabetes immunopathology using eye-transplanted islets in NOD mice.

AIMS/HYPOTHESIS: Autoimmune attack against the insulin-producing beta cells in the pancreatic islets results in type 1 diabetes. However, despite considerable research, details of the type 1 diabetes immunopathology in situ are not fully understood mainly because of difficult access to the pancreatic islets in vivo. METHODS: Here, we used direct non-invasive confocal imaging of islets transplanted in the anterior chamber of the eye (ACE) to investigate the anti-islet autoimmunity in NOD mice before, during and after diabetes onset. ACE-transplanted islets allowed longitudinal studies of the autoimmune attack against islets and revealed the infiltration kinetics and in situ motility dynamics of fluorescence-labelled autoreactive T cells during diabetes development. Ex vivo immunostaining was also used to compare immune cell infiltrations into islet grafts in the eye and kidney as well as in pancreatic islets of the same diabetic NOD mice. RESULTS: We found similar immune infiltration in native pancreatic and ACE-transplanted islets, which established the ACE-transplanted islets as reliable reporters of the autoimmune response. Longitudinal studies in ACE-transplanted islets identified in vivo hallmarks of islet inflammation that concurred with early immune infiltration of the islets and preceded their collapse and hyperglycaemia onset. A model incorporating data on ACE-transplanted islet degranulation and swelling allowed early prediction of the autoimmune attack in the pancreas and prompted treatments to intercept type 1 diabetes. CONCLUSIONS/INTERPRETATION: The current findings highlight the value of ACE-transplanted islets in studying early type 1 diabetes pathogenesis in vivo and underscore the need for timely intervention to halt disease progression.

Correction to: In vivo imaging of type 1 diabetes immunopathology using eye-transplanted islets in NOD mice.

Unfortunately there is a mistake in the presentation of the affiliations in this paper.

Glucose-stimulated insulin release: Parallel perifusion studies of free and hydrogel encapsulated human pancreatic islets.

To explore the effects immune-isolating encapsulation has on the insulin secretion of pancreatic islets and to improve our ability to quantitatively describe the glucose-stimulated insulin release (GSIR) of pancreatic islets, we conducted dynamic perifusion experiments with isolated human islets. Free (unencapsulated) and hydrogel encapsulated islets were perifused, in parallel, using an automated multi-channel system that allows sample collection with high temporal resolution. Results indicated that free human islets secrete less insulin per unit mass or islet equivalent (IEQ) than murine islets and with a less pronounced first-phase peak. While small microcapsules (d = 700 µm) caused only a slightly delayed and blunted first-phase insulin response compared to unencapsulated islets, larger capsules (d = 1,800 µm) completely blunted the first-phase peak and decreased the total amount of insulin released. Experimentally obtained insulin time-profiles were fitted with our complex insulin secretion computational model. This allowed further fine-tuning of the hormone-release parameters of this model, which was implemented in COMSOL Multiphysics to couple hormone secretion and nutrient consumption kinetics with diffusive and convective transport. The results of these GSIR experiments, which were also supported by computational modeling, indicate that larger capsules unavoidably lead to dampening of the first-phase insulin response and to a sustained-release type insulin secretion that can only slowly respond to changes in glucose concentration. Bioartificial pancreas type devices can provide long-term and physiologically desirable solutions only if immunoisolation and biocompatibility considerations are integrated with optimized nutrient diffusion and insulin release characteristics by design.

Design, Synthesis, and Evaluation of Novel Immunomodulatory Small Molecules Targeting the CD40⁻CD154 Costimulatory Protein-Protein Interaction.

We report the design, synthesis, and testing of novel small-molecule compounds targeting the CD40⁻CD154 (CD40L) costimulatory interaction for immunomodulatory purposes. This protein-protein interaction (PPI) is a TNF-superfamily (TNFSF) costimulatory interaction that is an important therapeutic target since it plays crucial roles in the activation of T cell responses, and there is resurgent interest in its modulation with several biologics in development. However, this interaction, just as all other PPIs, is difficult to target by small molecules. Following up on our previous work, we have now identified novel compounds such as DRI-C21091 or DRI-C21095 that show activity (IC50) in the high nanomolar to low micromolar range in the binding inhibition assay and more than thirty-fold selectivity versus other TNFSF PPIs including OX40⁻OX40L, BAFFR-BAFF, and TNF-R1-TNFα. Protein thermal shift (differential scanning fluorimetry) assays indicate CD154 and not CD40 as the binding partner. Activity has also been confirmed in cell assays and in a mouse model (alloantigen-induced T cell expansion in a draining lymph node). Our results expand the chemical space of identified small-molecule CD40⁻CD154 costimulatory inhibitors and provide lead structures that have the potential to be developed as orally bioavailable immunomodulatory therapeutics that are safer and less immunogenic than corresponding biologics.

Comprehensive Metabolomics Study To Assess Longitudinal Biochemical Changes and Potential Early Biomarkers in Nonobese Diabetic Mice That Progress to Diabetes.

A global nontargeted longitudinal metabolomics study was carried out in male and female NOD mice to characterize the time-profile of the changes in the metabolic signature caused by onset of type 1 diabetes (T1D) and identify possible early biomarkers in T1D progressors. Metabolomics profiling of samples collected at five different time-points identified 676 and 706 biochemicals in blood and feces, respectively. Several metabolites were expressed at significantly different levels in progressors at all time-points, and their proportion increased strongly following onset of hyperglycemia. At the last time-point, when all progressors were diabetic, a large percentage of metabolites had significantly different levels: 57.8% in blood and 27.8% in feces. Metabolic pathways most strongly affected included the carbohydrate, lipid, branched-chain amino acid, and oxidative ones. Several biochemicals showed considerable (>4×) change. Maltose, 3-hydroxybutyric acid, and kojibiose increased, while 1,5-anhydroglucitol decreased more than 10-fold. At the earliest time-point (6-week), differences between the metabolic signatures of progressors and nonprogressors were relatively modest. Nevertheless, several compounds had significantly different levels and show promise as possible early T1D biomarkers. They include fatty acid phosphocholine derivatives from the phosphatidylcholine subpathway (elevated in both blood and feces) as well as serotonin, ribose, and arabinose (increased) in blood plus 13-HODE, tocopherol (increased), diaminopimelate, valerate, hydroxymethylpyrimidine, and dulcitol (decreased) in feces. A combined metabolic signature based on these compounds might serve as an early predictor of T1D-progressors.

Metabolomics Study of the Effects of Inflammation, Hypoxia, and High Glucose on Isolated Human Pancreatic Islets.

The transplantation of human pancreatic islets is a therapeutic possibility for a subset of type 1 diabetic patients who experience severe hypoglycemia. Pre- and post-transplantation loss in islet viability and function, however, is a major efficacy-limiting impediment. To investigate the effects of inflammation and hypoxia, the main obstacles hampering the survival and function of isolated, cultured, and transplanted islets, we conducted a comprehensive metabolomics evaluation of human islets in parallel with dynamic glucose-stimulated insulin release (GSIR) perifusion studies for functional evaluation. Metabolomics profiling of media and cell samples identified a total of 241 and 361 biochemicals, respectively. Metabolites that were altered in highly significant manner in both included, for example, kynurenine, kynurenate, citrulline, and mannitol/sorbitol under inflammation (all elevated) plus lactate (elevated) and N-formylmethionine (depressed) for hypoxia. Dynamic GSIR experiments, which capture both first- and second-phase insulin release, found severely depressed insulin-secretion under hypoxia, whereas elevated baseline and stimulated insulin-secretion was measured for islet exposed to the inflammatory cytokine cocktail (IL-1ß, IFN-γ, and TNF-α). Because of the uniquely large changes observed in kynurenine and kynurenate, they might serve as potential biomarkers of islet inflammation, and indoleamine-2,3-dioxygenase on the corresponding pathway could be a worthwhile therapeutic target to dampen inflammatory effects.

Cell length growth patterns in fission yeast reveal a novel size control mechanism operating in late G2 phase.

BACKGROUND INFORMATION: Because cylindrically shaped fission yeast cells grow exclusively at their tips, cell volume is proportional to length and can be easily monitored by time-lapse microscopy. Here, we analysed the growth pattern of individual cells from several fission yeast strains to determine the growth function that describes them most adequately and to perform size control studies. RESULTS: The growth pattern of most cells during their growth period is best described by a bilinear function (i.e., two linear segments of different growth rates separated by a rate-change point). Linear growth patterns were also observed in several cases, but exponential ones only rarely. Since the bilinear patterns are separated into two segments by a breakpoint, we examined the existence of size control by regression analyses of the appropriate growth parameters in both segments. This confirmed the existence of known size controls in late G1, mid-G2 and late G2 during the fission yeast cycle. The present analyses also revealed that, contrary to the commonly accepted current view, late G2 size control is a general characteristic third event in the cycle. The level of the critical late G2 size that needs to be reached in an individual fission yeast cell is influenced by the growth rate of the cell in a manner similar to budding yeast, suggesting an evolutionary conserved mechanism. CONCLUSIONS: The present study of individual cell growth patterns in wild-type and several cell cycle mutant fission yeast strains confirmed that, for most cells, growth is best described by a bilinear function. Three different size control mechanisms were found to operate in the different strains, and, as a novel observation, cell size was always found to be monitored before mitotic onset, irrespective of the existence of any earlier size checkpoints. SIGNIFICANCE: Studying the pattern of growth and the mechanism of size control helps to clarify the connections between cell growth and division, since their coordination must work properly to maintain size homeostasis. In this study, we argue that most individual fission yeast cells grow following a bilinear pattern, and we confirm the existence of three different size control mechanisms.

Biphasic decline of ß-cell function with age in euglycemic nonobese diabetic mice parallels diabetes onset.

A gradual decline in insulin response is known to precede the onset of type 1 diabetes (T1D). To track age-related changes in the ß-cell function of nonobese diabetic (NOD) mice, the most commonly used animal model for T1D, and to establish differences between those who do and do not become hyperglycemic, we performed a long-term longitudinal oral glucose tolerance test (OGTT) study (10-42 weeks) in combination with immunofluorescence imaging of islet morphology and cell proliferation. We observed a clear biphasic decline in insulin secretion (AUC0-30 min ) even in euglycemic animals. A first phase (10-28 weeks) consisted of a relatively rapid decline and paralleled diabetes development in the same cohort of animals. This was followed by a second phase (29-42 weeks) during which insulin secretion declined much slower while no additional animals became diabetic. Blood glucose profiles showed a corresponding, but less pronounced change: the area under the concentration curve (AUC0-150 min ) increased with age, and fit with a bilinear model indicated a rate-change in the trendline around 28 weeks. In control NOD scids, no such changes were observed. Islet morphology also changed with age as islets become surrounded by mononuclear infiltrates, and, in all mice, islets with immune cell infiltration around them showed increased ß-cell proliferation. In conclusion, insulin secretion declines in a biphasic manner in all NOD mice. This trend, as well as increased ß-cell proliferation, is present even in the NODs that never become diabetic, whereas, it is absent in control NOD scid mice.

Experimental evaluation and computational modeling of the effects of encapsulation on the time-profile of glucose-stimulated insulin release of pancreatic islets.

BACKGROUND: In type 1 diabetic patients, who have lost their ability to produce insulin, transplantation of pancreatic islet cells can normalize metabolic control in a manner that is not achievable with exogenous insulin. To be successful, this procedure has to address the problems caused by the immune and autoimmune responses to the graft. Islet encapsulation using various techniques and materials has been and is being extensively explored as a possible approach. Within this framework, it is of considerable interest to characterize the effect encapsulation has on the insulin response of pancreatic islets. METHODS: To improve our ability to quantitatively describe the glucose-stimulated insulin release (GSIR) of pancreatic islets in general and of micro-encapsulated islets in particular, we performed dynamic perifusion experiments with frequent sampling. We used unencapsulated and microencapsulated murine islets in parallel and fitted the results with a complex local concentration-based finite element method (FEM) computational model. RESULTS: The high-resolution dynamic perifusion experiments allowed good characterization of the first-phase and second-phase insulin secretion, and we observed a slightly delayed and blunted first-phase insulin response for microencapsulated islets when compared to free islets. Insulin secretion profiles of both free and encapsulated islets could be fitted well by a COMSOL Multiphysics model that couples hormone secretion and nutrient consumption kinetics with diffusive and convective transport. This model, which was further validated and calibrated here, can be used for arbitrary geometries and glucose stimulation sequences and is well suited for the quantitative characterization of the insulin response of cultured, perifused, transplanted, or encapsulated islets. CONCLUSIONS: The present high-resolution GSIR experiments allowed for direct characterization of the effect microencapsulation has on the time-profile of insulin secretion. The multiphysics model, further validated here with the help of these experimental results, can be used to increase our understanding of the challenges that have to be faced in the design of bioartificial pancreas-type devices and to advance their further optimization.

Activity-limiting role of molecular size: size-dependency of maximum activity for P450 inhibition as revealed by qHTS data.

Analysis of a large number of data on cytochrome P450 (P450) inhibition obtained from quantitative high-throughput screening assays from the PubChem BioAssay Database clearly indicates that molecular size has an important activity-limiting role for datasets focused on drug-like compounds (PubChem BioAssay Identifier [AID] 1851) as well as for datasets also incorporating a wider range of environmental chemicals (AIDs 410, 899, 883, 891, and 884). Maximum inhibitory activity increases with size for small enough structures then plateaus and begins to show a decreasing trend for larger structures. Log-scaled maximum median inhibitory concentration (pIC50) as a function of molecular size could be fitted well with a bilinear model (LinBiExp), and the shape of the curve is quite similar across five P450 isozymes (CYP1A2, 2C9, 2C19, 2D6, and 3A4) with a turning-point of maximum inhibition around 300-500 Da. While the present size-based approach cannot account for the variability of activity in general, using data for a very large number of compounds, it still provides an intuitive interpretation of the maximum P450-inhibitory activity obtainable for a given molecular size and highlights the presence of an "optimum" size range.

Supervised Parametric Learning in the Identification of Composite Biomarker Signatures of Type 1 Diabetes in Integrated Parallel Multi-Omics Datasets.

BACKGROUND: Type 1 diabetes (T1D) is a devastating autoimmune disease, and its rising prevalence in the United States and around the world presents a critical problem in public health. While some treatment options exist for patients already diagnosed, individuals considered at risk for developing T1D and who are still in the early stages of their disease pathogenesis without symptoms have no options for any preventive intervention. This is because of the uncertainty in determining their risk level and in predicting with high confidence who will progress, or not, to clinical diagnosis. Biomarkers that assess one's risk with high certainty could address this problem and will inform decisions on early intervention, especially in children where the burden of justifying treatment is high. Single omics approaches (e.g., genomics, proteomics, metabolomics, etc.) have been applied to identify T1D biomarkers based on specific disturbances in association with the disease. However, reliable early biomarkers of T1D have remained elusive to date. To overcome this, we previously showed that parallel multi-omics provides a more comprehensive picture of the disease-associated disturbances and facilitates the identification of candidate T1D biomarkers. METHODS: This paper evaluated the use of machine learning (ML) using data augmentation and supervised ML methods for the purpose of improving the identification of salient patterns in the data and the ultimate extraction of novel biomarker candidates in integrated parallel multi-omics datasets from a limited number of samples. We also examined different stages of data integration (early, intermediate, and late) to assess at which stage supervised parametric models can learn under conditions of high dimensionality and variation in feature counts across different omics. In the late integration scheme, we employed a multi-view ensemble comprising individual parametric models trained over single omics to address the computational challenges posed by the high dimensionality and variation in feature counts across the different yet integrated multi-omics datasets. RESULTS: the multi-view ensemble improves the prediction of case vs. control and finds the most success in flagging a larger consistent set of associated features when compared with chance models, which may eventually be used downstream in identifying a novel composite biomarker signature of T1D risk. CONCLUSIONS: the current work demonstrates the utility of supervised ML in exploring integrated parallel multi-omics data in the ongoing quest for early T1D biomarkers, reinforcing the hope for identifying novel composite biomarker signatures of T1D risk via ML and ultimately informing early treatment decisions in the face of the escalating global incidence of this debilitating disease.

A Composite Biomarker Signature of Type 1 Diabetes Risk Identified via Augmentation of Parallel Multi-Omics Data from a Small Cohort.

Background: Biomarkers of early pathogenesis of type 1 diabetes (T1D) are crucial to enable effective prevention measures in at-risk populations before significant damage occurs to their insulin producing beta-cell mass. We recently introduced the concept of integrated parallel multi-omics and employed a novel data augmentation approach which identified promising candidate biomarkers from a small cohort of high-risk T1D subjects. We now validate selected biomarkers to generate a potential composite signature of T1D risk. Methods: Twelve candidate biomarkers, which were identified in the augmented data and selected based on their fold-change relative to healthy controls and cross-reference to proteomics data previously obtained in the expansive TEDDY and DAISY cohorts, were measured in the original samples by ELISA. Results: All 12 biomarkers had established connections with lipid/lipoprotein metabolism, immune function, inflammation, and diabetes, but only 7 were found to be markedly changed in the high-risk subjects compared to the healthy controls: ApoC1 and PON1 were reduced while CETP, CD36, FGFR1, IGHM, PCSK9, SOD1, and VCAM1 were elevated. Conclusions: Results further highlight the promise of our data augmentation approach in unmasking important patterns and pathologically significant features in parallel multi-omics datasets obtained from small sample cohorts to facilitate the identification of promising candidate T1D biomarkers for downstream validation. They also support the potential utility of a composite biomarker signature of T1D risk characterized by the changes in the above markers.

Drug Integrating Amphiphilic Nano-Assemblies: 2. Spatiotemporal Distribution within Inflammation Sites.

The need for chronic systemic immunosuppression, which is associated with unavoidable side-effects, greatly limits the applicability of allogeneic cell transplantation for regenerative medicine applications including pancreatic islet cell transplantation to restore insulin production in type 1 diabetes (T1D). Cell transplantation in confined sites enables the localized delivery of anti-inflammatory and immunomodulatory drugs to prevent graft loss by innate and adaptive immunity, providing an opportunity to achieve local effects while minimizing unwanted systemic side effects. Nanoparticles can provide the means to achieve the needed localized and sustained drug delivery either by graft targeting or co-implantation. Here, we evaluated the potential of our versatile platform of drug-integrating amphiphilic nanomaterial assemblies (DIANAs) for targeted drug delivery to an inflamed site model relevant for islet transplantation. We tested either passive targeting of intravenous administered spherical nanomicelles (nMIC; 20-25 nm diameter) or co-implantation of elongated nanofibrils (nFIB; 5 nm diameter and >1 µm length). To assess the ability of nMIC and nFIB to target an inflamed graft site, we used a lipophilic fluorescent cargo (DiD and DiR) and evaluated the in vivo biodistribution and cellular uptake in the graft site and other organs, including draining and non-draining lymph nodes, after systemic administration (nMIC) and/or graft co-transplantation (nFIB) in mice. Localized inflammation was generated either by using an LPS injection or by using biomaterial-coated islet-like bead implantation in the subcutaneous site. A cell transplant inflammation model was used as well to test nMIC- and nFIB-targeted biodistribution. We found that nMIC can reach the inflamed site after systemic administration, while nFIB remains localized for several days after co-implantation. We confirmed that DIANAs are taken up by different immune cell populations responsible for graft inflammation. Therefore, DIANA is a useful approach for targeted and/or localized delivery of immunomodulatory drugs to decrease innate and adaptive immune responses that cause graft loss after transplantation of therapeutic cells.

The promiscuous protein binding ability of erythrosine B studied by metachromasy (metachromasia).

The present study aims to elucidate aspects of the protein binding ability of erythrosine B (ErB), a poly-iodinated xanthene dye and an FDA-approved food colorant (FD&C Red No. 3), which we have identified recently as a promiscuous inhibitor of protein-protein interactions (PPIs) with a remarkably consistent median inhibitory concentration (IC50 ) in the 5- to 30-µM range. Because ErB exhibits metachromasy, that is, color change upon binding to several proteins, we exploited this property to quantify its binding to proteins such as bovine serum albumin (BSA) and CD40L (CD154) and to determine the corresponding binding constants (Kd ) and stoichiometry (nb ) using spectrophotometric methods. Binding was reversible, and the estimated affinities for both protein targets obtained here (Kd values of 14 and 20 µM for BSA and CD40L, respectively) were in good agreement with that expected from the PPI inhibitory activity of ErB. A stoichiometry greater than one was observed both for CD40L and BSA binding (nb of 5-6 and 8-9 for BSA and CD40L, respectively), indicating the possibility of nonspecific binding of the flat and rigid ErB molecule at multiple sites, which could explain the promiscuous PPI inhibitory activity if some of these overlap with the binding site of the protein partner and interfere with the binding.

Cell length growth in fission yeast: an analysis of its bilinear character and the nature of its rate change transition.

During their mitotic cycle, cylindrical fission yeast cells grow exclusively at their tips. Length growth starts at birth and halts at mitotic onset when the cells begin to prepare for division. While the growth pattern was initially considered to be exponential, during the last three decades an increasing amount of evidence indicated that it is rather a bilinear function [two linear segments separated by a rate change point (RCP)]. The main focus of this work was to clarify this and to elucidate the further question of whether the rate change occurs abruptly at the RCP or more smoothly during a transition period around it. We have analyzed the individual growth patterns obtained by time-lapse microscopy of 60 wild-type cells separately as well as that of the 'average' cell generated from their superposition. Linear, exponential, and bilinear functions were fitted to the data, and their suitability was compared using objective model selection criteria. This analysis found the overwhelming majority of the cells (70%) to have a bilinear growth pattern with close to half of them showing a smooth and not an abrupt transition. The growth pattern of the average cell was also found to be bilinear with a smooth transition.