OCT4 expression in human embryonic stem cells: spatio-temporal dynamics and fate transitions.

The improved in vitro regulation of human embryonic stem cell (hESC) pluripotency and differentiation trajectories is required for their promising clinical applications. The temporal and spatial quantification of the molecular interactions controlling pluripotency is also necessary for the development of successful mathematical and computational models. Here we use time-lapse experimental data of OCT4-mCherry fluorescence intensity to quantify the temporal and spatial dynamics of the pluripotency transcription factor OCT4 in a growing hESC colony in the presence and absence of BMP4. We characterise the internal self-regulation of OCT4 using the Hurst exponent and autocorrelation analysis, quantify the intra-cellular fluctuations and consider the diffusive nature of OCT4 evolution for individual cells and pairs of their descendants. We find that OCT4 abundance in the daughter cells fluctuates sub-diffusively, showing anti-persistent self-regulation. We obtain the stationary probability distributions governing hESC transitions amongst the different cell states and establish the times at which pro-fate cells (which later give rise to pluripotent or differentiated cells) cluster in the colony. By quantifying the similarities between the OCT4 expression amongst neighbouring cells, we show that hESCs express similar OCT4 to cells within their local neighbourhood within the first two days of the experiment and before BMP4 treatment. Our framework allows us to quantify the relevant properties of proliferating hESC colonies and the procedure is widely applicable to other transcription factors and cell populations.

Untargeted metabolomics for plasma biomarker discovery for early chronic kidney disease diagnosis in pediatric patients using LC-QTOF-MS.

Pediatric chronic kidney disease (CKD) is a clinical syndrome characterized by renal hypofunction occurring due to gradual and irreversible kidney damage that can further progress over time. New biomarkers may help early diagnosis of pediatric patients suffering from CKD and improve the outcome. Untargeted metabolomics based on LC-QTOF-MS has been used to find new biomarkers for the early diagnosis of CKD in plasma from pediatric patients. In order to avoid any bias in the determination of statistically significant entities as a consequence of the data analysis method followed, two different chemometric approaches have been used, Mass Profiler Professional (MPP) software and Matlab R2015a software. Metabolic fingerprints of control and CKD pediatric patients were compared and five metabolites which showed a significant change common to both data analysis procedures were identified. Sphingosine-1-phosphate, n-butyrylcarnitine, cis-4-decenoylcarnitine and an unidentified feature with 126.0930 m/z were found to be increased in plasma from pediatric patients with CKD, whereas bilirubin was significantly decreased. A partial least squares discriminant analysis model built with these 5 entities classified correctly 96% of the samples. In addition, when considering only early CKD patients against controls, a performance of 97% was obtained. Thus, these promising metabolites could be suitable biomarkers for the early diagnosis of pediatric CKD in a clinical setting.

Phase-field modelling of the dynamics of Z-ring formation in liposomes: Onset of constriction and coarsening.

We propose a model for the dynamics of the formation of rings of FtsZ on tubular liposomes which produce constriction on the corresponding membrane. Our phase-field model is based on a simple bending energy that captures the dynamics of the interplay between the protein and the membrane. The short-time regime is analyzed by a linear dispersion relation, with which we are able to predict the number of rings per unit length on a tubular liposome. We study numerically the long-time dynamics of the system in the non-linear regime where we observe coarsening of Z-rings on tubular liposomes. In particular, our numerical results show that, during the coarsening process, the number of Z-rings decreases as the radius of tubular liposome increases. This is consistent with the experimental observation that the separation between rings is proportional to the radius of the liposome. Our model predicts that the mechanism for the increased rate of coarsening in liposomes of larger radius is a consequence of the increased interface energy.

A prospective study on implants installed with flapless-guided surgery using the all-on-four concept in the mandible.

AIM: Clinical data are scarce on flapless-guided surgery in the mandible using the all-on-four concept. In addition, limited documentation exists on the latter under immediate loading conditions with a pre-fabricated implant bridge. The aim was to provide detailed documentation focusing on clinical and radiographic outcome and complications. MATERIAL AND METHODS: Sixteen systemically healthy non-smoking patients (10 women, 6 men, average age 59 years) with sufficient bone volume in the mandible were operated via flapless-guided surgery using the all-on-four concept. Clinical and radiographic data and complications were registered at 3, 6 and 12 months. RESULTS: The overall implant survival rate was 90% with a trend for higher failure of short implants (P = 0.098). The mean bone level after 12 months of function was 0.83 mm with a maximum of 1.07 mm. Technical complications were common (15/16 patients). These mainly related to a misfit between the pre-fabricated prosthesis and abutment(s) (13/16 patients). CONCLUSION: If immediate loading of implants is pursued fabrication of the implant bridge should be based on actual impression of the implants at the time of surgery and not on their virtual position.

Mathematical birth of Early Afterdepolarizations in a cardiomyocyte model.

Early Afterdepolarizations (EADs) are abnormal behaviors that can lead to cardiac failure and even cardiac death. In this paper we investigate the occurrence and development of these phenomena in a reduced Luo-Rudy cardiac model. Through a comprehensive dynamical analysis, we map out the distinct patterns observed in the parametric plane, differentiating between normal beats without EADs and pathological beats with EADs. By examining the bifurcation structure of the model, we elucidate the dynamical elements associated with these patterns and their transitions. Using a fast-slow analysis, we explore the emergence and evolution of EADs in the model. Notably, our approach combines the two commonly used fast-slow approaches (1-slow-2-fast and 2-slow-1-fast), and we show how both approaches together provide a more complete understanding of this phenomenon.

Modelling the interplay of SARS-CoV-2 variants in the United Kingdom.

Many COVID-19 vaccines are proving to be highly effective to prevent severe disease and to diminish infections. Their uneven geographical distribution favors the appearance of new variants of concern, as the highly transmissible Delta variant, affecting particularly non-vaccinated people. It is important to device reliable models to analyze the spread of the different variants. A key factor is to consider the effects of vaccination as well as other measures used to contain the pandemic like social behaviour. The stochastic geographical model presented here, fulfills these requirements. It is based on an extended compartmental model that includes various strains and vaccination strategies, allowing to study the emergence and dynamics of the new COVID-19 variants. The model conveniently separates the parameters related to the disease from the ones related to social behavior and mobility restrictions. We applied the model to the United Kingdom by using available data to fit the recurrence of the currently prevalent variants. Our computer simulations allow to describe the appearance of periodic waves and the features that determine the prevalence of certain variants. They also provide useful predictions to help planning future vaccination boosters. We stress that the model could be applied to any other country of interest.

Strategies for COVID-19 vaccination under a shortage scenario: a geo-stochastic modelling approach.

In a world being hit by waves of COVID-19, vaccination is a light on the horizon. However, the roll-out of vaccination strategies and their influence on the pandemic are still open questions. In order to compare the effect of various strategies proposed by the World Health Organization and other authorities, a previously developed SEIRS stochastic model of geographical spreading of the virus is extended by adding a compartment for vaccinated people. The parameters of the model were fitted to describe the pandemic evolution in Argentina, Mexico and Spain to analyze the effect of the proposed vaccination strategies. The mobility parameters allow to simulate different social behaviors (e.g. lock-down interventions). Schemes in which vaccines are applied homogeneously in all the country, or limited to the most densely-populated areas, are simulated and compared. The second strategy is found to be more effective. Moreover, under the current global shortage of vaccines, it should be remarked that immunization is enhanced when mobility is reduced. Additionally, repetition of vaccination campaigns should be timed considering the immunity lapse of the vaccinated (and recovered) people. Finally, the model is extended to include the effect of isolation of detected positive cases, shown to be important to reduce infections.

A linear-polymer-based lactoferrin-selective recognition element for an ELISA mimic: A proof of concept.

The synthesis of polymers with tailored properties for the recognition of macromolecules such as proteins is challenging. In this work, the synthesis of a new polymer format, a linear polymer (LP), as the selective recognition element for the globular protein lactoferrin (LF) is proposed as a proof-of-concept study. For the synthesis, a solid-phase strategy using the reversible deactivation radical polymerisation (RDRP) mechanism is proposed. This approach, which is usually used in molecular imprinting, involves the immobilisation of LF on the surface of a solid support, but, unlike classical imprinting, a cross-linker in the polymerisation mixture is not required. Consequently, the copolymer is soluble and flexible, thus overcoming the drawbacks associated with traditional synthetic polymers for macromolecule imprinting. This new polymer format has great potential for replacing natural antibodies in bioassays such as enzyme-linked immunosorbent assays (ELISA), dot blot, western blot, or pull-down. In our case, the linear polymer was used as a recognition element to replace natural antibodies in a LF-selective ELISA. The responses of the linear polymer between LF concentrations of 0.1 nM and 0.25 µM were studied, and a significant difference was observed between the non-specific signals and the signals measured in the presence of the polymeric material. Further, the response versus log concentration curves were fitted to a logistic equation, allowing estimation of the EC50 value: 11.8 ± 1.4 nM. We also confirmed the selective detection of LF using the competitive inhibition of the selective LF-biotin conjugate (LF-Bi) binding to the plastic receptor (LP) for closely related proteins (e.g. those having similar molecular weights or isoelectric points) such as human lysozyme, trypsin, and albumin, which are present in human body fluids. The system presents a cross-reactivity value or selectivity of 1.95% for lysozyme, 0.028% for trypsin, and 0.016% for albumin. The applicability of this method for the determination of urine LF levels in inflammatory and infectious diseases of the human urinary tract is also demonstrated.

Detecting infected asymptomatic cases in a stochastic model for spread of Covid-19: the case of Argentina.

We have studied the dynamic evolution of the Covid-19 pandemic in Argentina. The marked heterogeneity in population density and the very extensive geography of the country becomes a challenge itself. Standard compartment models fail when they are implemented in the Argentina case. We extended a previous successful model to describe the geographical spread of the AH1N1 influenza epidemic of 2009 in two essential ways: we added a stochastic local mobility mechanism, and we introduced a new compartment in order to take into account the isolation of infected asymptomatic detected people. Two fundamental parameters drive the dynamics: the time elapsed between contagious and isolation of infected individuals ([Formula: see text]) and the ratio of people isolated over the total infected ones (p). The evolution is more sensitive to the [Formula: see text]parameter. The model not only reproduces the real data but also predicts the second wave before the former vanishes. This effect is intrinsic of extensive countries with heterogeneous population density and interconnection.The model presented has proven to be a reliable predictor of the effects of public policies as, for instance, the unavoidable vaccination campaigns starting at present in the world an particularly in Argentina.

The dynamics of shapes of vesicle membranes with time dependent spontaneous curvature.

We study the time evolution of the shape of a vesicle membrane under time-dependent spontaneous curvature by means of phase-field model. We introduce the variation in time of the spontaneous curvature via a second field which represents the concentration of a substance that anchors with the lipid bilayer thus changing the local curvature and producing constriction. This constriction is mediated by the action on the membrane of an structure resembling the role of a Z ring. Our phase-field model is able to reproduce a number of different shapes that have been experimentally observed. Different shapes are associated with different constraints imposed upon the model regarding conservation of membrane area. In particular, we show that if area is conserved our model reproduces the so-called L-form shape. By contrast, if the area of the membrane is allowed to grow, our model reproduces the formation of a septum in the vicinity of the constriction. Furthermore, we propose a new term in the free energy which allows the membrane to evolve towards eventual pinching.

Monogenic and polygenic models detected in steroid 21-hydroxylase deficiency-related paediatric hyperandrogenism.

AIMS: Hyperandrogenism, although mostly due to polygenic interactions, is monogenic for some enzymatic adrenal deficiencies. This study evaluates mono- and biallelic 21-hydroxylase deficiency (21OHD)-related hyperandrogenism in pediatric patients. Sensitizing and protective polymorphisms were investigated in carriers and cryptic forms of 21OHD. METHODS: The study involved a monogenic analysis of CYP21A2 in patients (375 nonclassical 21OHD [NC21OHD] children; 306 hyperandrogenic 21OHD carriers, n = 306) and a polygenic association study (CAPN10-UCSNP44, PON1-108, TNFR2-M196R, IGF2-ApaI and IRS1-G972R polymorphisms) of 170 hyperandrogenic carriers plus 277 family members (control groups). The metabolic marker 17OH progesterone defined the degree of deficiency; clinical expressivity was determined by pediatric endocrinologists. RESULTS: The group of 21OHD carriers manifesting hyperandrogenism was enriched in the CAPN-UCSNP44 rare variant in homozygosity (4.9 vs. 0.4%, NCBI data for the general population; p = 0.004). In our patients and controls, contrasting distributions were observed for this and another polymorphism, TNFR2-196R. In a recessive model, their rare variants were more frequently detected among the forms with high (p = 0.048) and low (p = 0.034) expressivity respectively. CONCLUSIONS: 21OHD-related pediatric hyperandrogenism follows monogenic and polygenic models. The opposite behaviors in terms of clinical expressivity detected for CAPN-UCSNP44 and TNFR2-M196R rare variants suggest these variants to be sensitizing and protective factors respectively in adrenal hyperandrogenism.

Dynamics of reaction-diffusion systems in a subdiffusive regime.

In this paper, we examine the dynamics of reaction-diffusion systems with fractional time derivatives. It is shown that in these conditions diffusion is anomalous, in the sense that the mean-square displacement r2 approximately tgamma, where gamma<1, a situation known as subdiffusion. We study the conditions for the appearance of a diffusion-driven instability and show that the restrictive conditions for a Turing instability are relaxed. This implies that systems whose kinetics are not of the activator-inhibitor kind can have a Turing instability and a modulated final state. We demonstrate our results with numerical calculations in two dimensions using a generic Turing model.

LC-QQQ-MS routine analysis method for new biomarker quantification in plasma aimed at early chronic kidney disease diagnosis.

Pediatric chronic kidney disease (CKD) is currently assessed using glomerular filtration rate (GFR), which is calculated from different equations based on serum creatinine concentration. However, serum creatinine is affected by several factors and is not reliable enough for the diagnosis of CKD, especially at early stages. Recent targeted and untargeted metabolomics studies found 7 new potential biomarkers that could be useful for early pediatric chronic kidney disease diagnosis. Thus, a new LC-QQQ-MS analytical method has been developed and validated aimed at routine analysis of these 7 potential biomarkers: NG,NG'-dimethyl-l-arginine di(p-hydroxyazobenzene-p'-sulfonate) (SDMA), S-adenosyl-l-methionine (SAM), n-butyryl-l-carnitine (nC4), iso-butyryl-l-carnitine (iC4), citrulline (CIT), creatinine (CNN) and d-erytro-sphingosine-1-phosphate (S1P), in addition to creatinine, the classical biomarker for CKD diagnosis. Then, this analytical method has been used for the quantification of plasma samples from a heterogeneous group of CKD pediatric patients and a control pediatric population. Data analysis of these results showed that it is possible to differentiate between CKD and control populations based on the metabolite concentration in plasma.

Generation of ECG signals from a reaction-diffusion model spatially discretized.

We propose a model to generate electrocardiogram signals based on a discretized reaction-diffusion system to produce a set of three nonlinear oscillators that simulate the main pacemakers in the heart. The model reproduces electrocardiograms from healthy hearts and from patients suffering various well-known rhythm disorders. In particular, it is shown that under ventricular fibrillation, the electrocardiogram signal is chaotic and the transition from sinus rhythm to chaos is consistent with the Ruelle-Takens-Newhouse route to chaos, as experimental studies indicate. The proposed model constitutes a useful tool for research, medical education, and clinical testing purposes. An electronic device based on the model was built for these purposes.

Spinach consumption ameliorates the gut microbiota and dislipaemia in rats with diet-induced non-alcoholic fatty liver disease (NAFLD).

Non-alcoholic fatty liver disease (NAFLD) is defined as the accumulation of fat in liver cells, which causes serious health consequences. Animal and human studies suggest that the gut microbiota plays a role in the pathogenesis of NAFLD. Here, we investigated whether spinach consumption could ameliorate high-fat-diet-induced disturbances in certain intestinal bacterial groups and products derived from their metabolism, such as short-chain fatty acids (SCFAs) and microbial phenolic catabolites. Attention is also paid to blood lipids and glucose. In the study, a rat model of high-fat-diet-induced NAFLD was used. There were six experimental groups: NC (normal diet), NB (normal diet + 2.5% spinach), NA (normal diet + 5% spinach), HC (high-fat diet), HB (high-fat diet + 2.5% spinach) and HA (high-fat diet + 5% spinach). The rats consumed these diets for five weeks, and after that, they were sacrificed and plasma, urine, intestinal content, faeces and liver samples were taken. Biochemical parameters were analyzed in plasma, phenolic catabolites were quantified in the faeces, urine, plasma and liver by UPLC-ESI-MS/MS, and the analysis of the microbiota and SCFAs in the intestinal content was performed by qPCR and GLC. Consumption of a high-fat diet caused NAFLD and dislipaemia and altered the gut microbiota and the pattern of SCFAs and phenolic gut microbial catabolites. Supplementation with spinach partially ameliorated some alterations induced by the high-fat diet, in particular by increasing the Lactobacillus counts, reducing the fasting glucose and total and LDL-cholesterol and preventing excess liver cholesterol accumulation, thereby improving the values of the steatosis biomarkers.

Plasma biomarker discovery for early chronic kidney disease diagnosis based on chemometric approaches using LC-QTOF targeted metabolomics data.

Chronic kidney disease (CKD) is a progressive pathological condition in which renal function deteriorates in time. The first diagnosis of CKD is often carried out in general care attention by general practitioners by means of serum creatinine (CNN) levels. However, it lacks sensitivity and thus, there is a need for new robust biomarkers to allow the detection of kidney damage particularly in early stages. Multivariate data analysis of plasma concentrations obtained from LC-QTOF targeted metabolomics method may reveal metabolites suspicious of being either up-regulated or down-regulated from urea cycle, arginine methylation and arginine-creatine metabolic pathways in CKD pediatrics and controls. The results show that citrulline (CIT), symmetric dimethylarginine (SDMA) and S-adenosylmethionine (SAM) are interesting biomarkers to support diagnosis by CNN: early CKD samples and controls were classified with an increase in classification accuracy of 18% when using these 4 metabolites compared to CNN alone. These metabolites together allow classification of the samples into a definite stage of the disease with an accuracy of 74%, being the 90% of the misclassifications one level above or below the CKD stage set by the nephrologists. Finally, sex-related, age-related and treatment-related effects were studied, to evaluate whether changes in metabolite concentration could be attributable to these factors, and to correct them in case a new equation is developed with these potential biomarkers for the diagnosis and monitoring of pediatric CKD.

A study of the prebiotic-like effects of tomato juice consumption in rats with diet-induced non-alcoholic fatty liver disease (NAFLD).

Gut microbiota may play a role in the pathogenesis of NAFLD. We investigated whether tomato juice consumption for 5 weeks could ameliorate high-fat diet-induced alterations in certain intestinal bacterial groups and products arising from their metabolism (short-chain fatty acids and microbial phenolic catabolites). For this, we used a rat model with NAFLD induced by a high-fat diet, involving four experimental groups: NA (standard diet and water), NL (standard diet and tomato juice), HA (high-fat diet and water) and HL (high-fat diet and tomato juice). The onset of NAFLD impacted the gut microbiota profile, reducing the abundance of Bifidobacterium and Lactobacillus and increasing that of Enterobacteriaceae. Also, reduced concentrations of propionate, butyrate and phenolic catabolites and an increased acetate to propionate (Ac : Pr) ratio were observed. Tomato juice intake partially ameliorated high-fat diet-induced disturbances, particularly by increasing Lactobacillus abundance and diminishing the Ac : Pr ratio, suggesting a potential improvement of the metabolic pattern of NAFLD.

Wave-front dynamics in systems with directional anomalous diffusion.

In this paper we study the solutions of a generalized reaction-diffusion system with a bistable reaction term, and considering directional anomalous diffusion. We use the well-known properties of fractional derivatives to model asymmetric anomalous diffusion, and obtain traveling wave solutions that propagate in a direction that depends on the metastability of the front, the fractional exponent and the asymmetry of the diffusion.

Function of the spalt/spalt-related gene complex in positioning the veins in the Drosophila wing.

Spalt and Spalt-related encode conserved Zn-finger proteins that mediate the function of the TGF-beta molecule Decapentaplegic during the positioning of veins in the Drosophila wing. Here we show that Spalt and Spalt-related regulate the vein-specific expression of the transcription factors of the knirps and iroquois gene complexes, delimiting their domains of expression in the wing pouch. The effects of spalt/spalt-related mutations on knirps and iroquois expression are cell-autonomous, suggesting that they could be direct. The regulation of iroquois involves transcriptional repression by Spalt and Spalt-related, whereas the regulation of knirps involves a combination of transcriptional activation and repression mediated by the same genes. We suggest that the regulation of the iroquois and knirps gene complexes by Spalt and Spalt-related translates the Decapentaplegic morphogenetic gradient into precisely spaced pattern elements.

Therapy with insulin glargine (Lantus) in toddlers, children and adolescents with type 1 diabetes.

OBJECTIVE: To determine the efficacy and safety of insulin glargine (IG) in children and adolescents with type 1 diabetes. In a prospective, 6-month study, 80 patients, aged 2-19 years, received IG once daily plus insulin regular or rapid analogue before meals. The data of body mass index, frequency of severe hypoglycaemia, daily mean blood glucose, fasting blood glucose, haemoglobin A1c and total daily insulin dosage before and after institution of glargine therapy were collected. RESULTS: After 6 months, the average HbA1c level in the entire cohort dropped from 7.63+/-0.81 to 7.14+/-0.70% (p<0.001). Fasting blood glucose decreased from 161+/-37 to 150+/-35 mg/dl (p<0.05) in the total group. Severe hypoglycaemic episodes were reduced from 0.18 events per patient in the 6 months before IG therapy to 0.11 events per patient in the 6 months after IG therapy. The total daily insulin dose was reduced in the entire group from 0.90+/-0.32 to 0.83+/-0.29 u/kg/day (p<0.05). Body mass index (BMI) remained unchanged. In the 14 preschooler children, the HbA1c dropped from 7.54+/-0.60 to 6.96+/-0.57% (p<0.05). CONCLUSIONS: Insulin glargine is an efficacious treatment to improve metabolic control in children and adolescents with type 1 diabetes. It also improved the metabolic control in preschool-age children, without increasing the number of hypoglycaemic events.