Potential of animal-welfare compliant and sustainably sourced serum from pig slaughter blood.

The animal product most used as a stimulatory additive for cell cultivation is still fetal bovine serum (FBS). Besides the ethical concerns regarding serum collection, the main problems of FBS are batch-to-batch variability and the resulting risk of lower reproducibility, the differences between species, the presence of undefined/unknown components, and the risk of contamination. In contrast, pig blood, which is a by-product of slaughter, is a sufficiently available and sustainable resource with a high degree of standardization in terms of donor age, weight, and genetics. The variations in preparations from pig slaughter blood seem to be comparatively low, and consequently, batch effects might be much smaller, suggesting that the reproducibility of the research data obtained may be increased. Our pilot study aimed to investigate, as a proof of concept, whether adult human and porcine stem cells of different tissue origins proliferate and differentiate adequately when FBS is completely or partially replaced by porcine serum (PS). We could show that the human and porcine stem cells were vital and proliferated under partial and full PS supplementation. Furthermore, using PS, the two cell types studied showed tissue-specific differentiation (i.e., lipid vacuoles as a sign of adipogenic or myotubes as a sign of myogenic differentiation). In conclusion, the pig slaughter blood-derived serum has promising potential to be a replacement for FBS in adult stem cell cultures. Therefore, it could serve as a basis for the development of new cell culture supplements.

Viscosity Modeling for Blood and Blood Analog Fluids in Narrow Gap and High Reynolds Numbers Flows.

For the optimization of ventricular assist devices (VADs), flow simulations are crucial. Typically, these simulations assume single-phase flow to represent blood flow. However, blood consists of plasma and blood cells, making it a multiphase flow. Cell migration in such flows leads to a heterogeneous cell distribution, significantly impacting flow dynamics, especially in narrow gaps of less than 300 µm found in VADs. In these areas, cells migrate away from the walls, forming a cell-free layer, a phenomenon not usually considered in current VAD simulations. This paper addresses this gap by introducing a viscosity model that accounts for cell migration in microchannels under VAD-relevant conditions. The model is based on local particle distributions measured in a microchannels with a blood analog fluid. We developed a local viscosity distribution for flows with particles/cells and a cell-free layer, applicable to both blood and analog fluids, with particle volume fractions of up to 5%, gap heights of 150 µm, and Reynolds numbers around 100. The model was validated by comparing simulation results with experimental data of blood and blood analog fluid flow on wall shear stresses and pressure losses, showing strong agreement. This model improves the accuracy of simulations by considering local viscosity changes rather than assuming a single-phase fluid. Future developments will extend the model to physiological volume fractions up to 40%.

Management of Neurogenic Respiratory Alkalosis and Concomitant Lactatemia After Resection of a Posterior Fossa Meningioma: A Case Report.

Central neurogenic hyperventilation (CNH) is a rare disease, caused by chemical or mechanical disturbance of respiratory centers. It is characterized by the absence of extracerebral respiratory stimuli. A woman developed severe respiratory alkalosis and lactatemia after resection of a posterior fossa meningioma despite lack of cardio-respiratory or metabolic alterations. Cerebral computed tomography (cCT) revealed edema of the pontomedullary area. Treatment with mannitol and dexamethasone reestablished normal breathing patterns. Lactatemia was likely due to reduced splanchnic lactate utilization. Intracranial pathologies should be suspected in case of hyperventilation without overt reasons. cCT to confirm edema or ischemia and prompt treatment is suggested.

Optimized finite-time work protocols for the Higgs RNA model with external force.

The Higgs RNA model with an added term for a coupling to an external force is studied in regard to finite-time force-driving protocols with a minimal-work requirement. In this paper, RNA sequences which at low temperature exhibit hairpins are considered, which are often cited as typical template systems in stochastic thermodynamics. The optimized work protocols for this glassy many-particle system are determined numerically using the parallel tempering method. The protocols show distinct jumps at the beginning and end, which have been observed for single-particle systems and are proven to be optimal in the fast protocol limit generally. Optimality seems to be achieved by staying close to the equilibrium unfolding transition point, in agreement with experimental and theoretical observations. The change of work distributions, compared to those resulting from a naive linear driving protocol, are discussed generally and in terms of free energy estimation as well as the effect of optimized protocols on rare work process starting conditions.

Probing the large deviations for the beta random walk in random medium.

We consider a discrete-time random walk on a one-dimensional lattice with space- and time-dependent random jump probabilities, known as the beta random walk. We are interested in the probability that, for a given realization of the jump probabilities (a sample), a walker starting at the origin at time t=0 is at position beyond ξsqrt[T/2] at time T. This probability fluctuates from sample to sample and we study the large-deviation rate function, which characterizes the tails of its distribution at large time T≫1. It is argued that, up to a simple rescaling, this rate function is identical to the one recently obtained exactly by two of the authors for the continuum version of the model. That continuum model also appears in the macroscopic fluctuation theory of a class of lattice gases, e.g., in the so-called KMP model of heat transfer. An extensive numerical simulation of the beta random walk, based on an importance sampling algorithm, is found in good agreement with the detailed analytical predictions. A first-order transition in the tilted measure, predicted to occur in the continuum model, is also observed in the numerics.

First-passage area distribution and optimal fluctuations of fractional Brownian motion.

We study the probability distribution P(A) of the area A=∫_{0}^{T}x(t)dt swept under fractional Brownian motion (fBm) x(t) until its first passage time T to the origin. The process starts at t=0 from a specified point x=L. We show that P(A) obeys exact scaling relation P(A)=D^{1/2H}/L^{1+1/H}Φ_{H}(D^{1/2H}A/L^{1+1/H}), where 0

Current fluctuations in stochastically resetting particle systems.

We consider a system of noninteracting particles on a line with initial positions distributed uniformly with density ρ on the negative half-line. We consider two different models: (i) Each particle performs independent Brownian motion with stochastic resetting to its initial position with rate r and (ii) each particle performs run-and-tumble motion, and with rate r its position gets reset to its initial value and simultaneously its velocity gets randomized. We study the effects of resetting on the distribution P(Q,t) of the integrated particle current Q up to time t through the origin (from left to right). We study both the annealed and the quenched current distributions and in both cases, we find that resetting induces a stationary limiting distribution of the current at long times. However, we show that the approach to the stationary state of the current distribution in the annealed and the quenched cases are drastically different for both models. In the annealed case, the whole distribution P_{an}(Q,t) approaches its stationary limit uniformly for all Q. In contrast, the quenched distribution P_{qu}(Q,t) attains its stationary form for QQ_{crit}(t). We show that Q_{crit}(t) increases linearly with t for large t. On the scale where Q∼Q_{crit}(t), we show that P_{qu}(Q,t) has an unusual large deviation form with a rate function that has a third-order phase transition at the critical point. We have computed the associated rate functions analytically for both models. Using an importance sampling method that allows to probe probabilities as tiny as 10^{-14000}, we were able to compute numerically this nonanalytic rate function for the resetting Brownian dynamics and found excellent agreement with our analytical prediction.

Large-deviations of disease spreading dynamics with vaccination.

We numerically simulated the spread of disease for a Susceptible-Infected-Recovered (SIR) model on contact networks drawn from a small-world ensemble. We investigated the impact of two types of vaccination strategies, namely random vaccination and high-degree heuristics, on the probability density function (pdf) of the cumulative number C of infected people over a large range of its support. To obtain the pdf even in the range of probabilities as small as 10-80, we applied a large-deviation approach, in particular the 1/t Wang-Landau algorithm. To study the size-dependence of the pdfs within the framework of large-deviation theory, we analyzed the empirical rate function. To find out how typical as well as extreme mild or extreme severe infection courses arise, we investigated the structures of the time series conditioned to the observed values of C.

Systematic estimation of biological age of in vitro cell culture systems by an age-associated marker panel.

Aging is a process that affects almost all multicellular organisms and since our population ages with increasing prevalence of age-related diseases, it is important to study basic processes involved in aging. Many studies have been published so far using different and often single age markers to estimate the biological age of organisms or different cell culture systems. However, comparability of studies is often hampered by the lack of a uniform panel of age markers. Consequently, we here suggest an easy-to-use biomarker-based panel of classical age markers to estimate the biological age of cell culture systems that can be used in standard cell culture laboratories. This panel is shown to be sensitive in a variety of aging conditions. We used primary human skin fibroblasts of different donor ages and additionally induced either replicative senescence or artificial aging by progerin overexpression. Using this panel, highest biological age was found for artificial aging by progerin overexpression. Our data display that aging varies depending on cell line and aging model and even from individual to individual showing the need for comprehensive analyses.

Variational kinetic clustering of complex networks.

Efficiently identifying the most important communities and key transition nodes in weighted and unweighted networks is a prevalent problem in a wide range of disciplines. Here, we focus on the optimal clustering using variational kinetic parameters, linked to Markov processes defined on the underlying networks, namely, the slowest relaxation time and the Kemeny constant. We derive novel relations in terms of mean first passage times for optimizing clustering via the Kemeny constant and show that the optimal clustering boundaries have equal round-trip times to the clusters they separate. We also propose an efficient method that first projects the network nodes onto a 1D reaction coordinate and subsequently performs a variational boundary search using a parallel tempering algorithm, where the variational kinetic parameters act as an energy function to be extremized. We find that maximization of the Kemeny constant is effective in detecting communities, while the slowest relaxation time allows for detection of transition nodes. We demonstrate the validity of our method on several test systems, including synthetic networks generated from the stochastic block model and real world networks (Santa Fe Institute collaboration network, a network of co-purchased political books, and a street network of multiple cities in Luxembourg). Our approach is compared with existing clustering algorithms based on modularity and the robust Perron cluster analysis, and the identified transition nodes are compared with different notions of node centrality.

Biomarkers of geroprotection and cardiovascular health: An overview of omics studies and established clinical biomarkers in the context of diet.

The slowdown, inhibition, or reversal of age-related decline (as a composite of disease, dysfunction, and, ultimately, death) by diet or natural compounds can be defined as dietary geroprotection. While there is no single reliable biomarker to judge the effects of dietary geroprotection, biomarker signatures based on omics (epigenetics, gene expression, microbiome composition) are promising candidates. Recently, omic biomarkers started to supplement established clinical ones such as lipid profiles and inflammatory cytokines. In this review, we focus on human data. We first summarize the current take on genetic biomarkers based on epidemiological studies. However, most of the remaining biomarkers that we describe, whether omics-based or clinical, are related to intervention studies. Then, because of their promising potential in the context of dietary geroprotection, we focus on the effects of berry-based interventions, which up to now have been mostly described employing clinical markers. We provide an aggregation and tabulation of all the recent systematic reviews and meta-analyses that we could find related to this topic. Finally, we present evidence for the importance of the "nutribiography," that is, the influence that an individual's history of diet and natural compound consumption can have on the effects of dietary geroprotection.Supplemental data for this article is available online at https://doi.org/10.1080/10408398.2021.1975638.

A conserved long-distance telomeric silencing mechanism suppresses mTOR signaling in aging human fibroblasts.

Telomeres are repetitive nucleotide sequences at the ends of each chromosome. It has been hypothesized that telomere attrition evolved as a tumor suppressor mechanism in large long-lived species. Long telomeres can silence genes millions of bases away through a looping mechanism called telomere position effect over long distances (TPE-OLD). The function of this silencing mechanism is unknown. We determined a set of 2322 genes with high positional conservation across replicatively aging species that includes known and candidate TPE-OLD genes that may mitigate potentially harmful effects of replicative aging. Notably, we identified PPP2R2C as a tumor suppressor gene, whose up-regulation by TPE-OLD in aged human fibroblasts leads to dephosphorylation of p70S6 kinase and mammalian target of rapamycin suppression. A mechanistic link between telomeres and a tumor suppressor mechanism supports the hypothesis that replicative aging fulfills a tumor suppressor function and motivates previously unknown antitumor and antiaging strategies.

Large deviations of a susceptible-infected-recovered model around the epidemic threshold.

We numerically study the dynamics of the SIR disease model on small-world networks by using a large-deviation approach. This allows us to obtain the probability density function of the total fraction of infected nodes and of the maximum fraction of simultaneously infected nodes down to very small probability densities like 10^{-2500}. We analyze the structure of the disease dynamics and observed three regimes in all probability density functions, which correspond to quick mild, quick extremely severe, and sustained severe dynamical evolutions, respectively. Furthermore, the mathematical rate functions of the densities are investigated. The results indicate that the so-called large-deviation property holds for the SIR model. Finally, we measured correlations with other quantities like the duration of an outbreak or the peak position of the fraction of infections, also in the rare regions which are not accessible by standard simulation techniques.

Differential Effects of Speech and Language Therapy and rTMS in Chronic Versus Subacute Post-stroke Aphasia: Results of the NORTHSTAR-CA Trial.

BACKGROUND & OBJECTIVE: Contralesional 1-Hz repetitive transcranial magnetic stimulation (rTMS) over the right pars triangularis combined with speech-language therapy (SLT) has shown positive results on the recovery of naming in subacute (5-45 days) post-stroke aphasia. NORTHSTAR-CA is an extension of the previously reported NORTHSTAR trial to chronic aphasia (>6 months post-stroke) designed to compare the effectiveness of the same rTMS protocol in both phases. METHODS: Sixty-seven patients with left middle cerebral artery infarcts (28 chronic, 39 subacute) were recruited (01-2014 to 07-2019) and randomized to receive rTMS (N = 34) or sham stimulation (N = 33) with SLT for 10 days. Primary outcome variables were Z-score changes in naming, semantic fluency and comprehension tests and adverse event frequency. Intention-to-treat analyses tested between-group effects at days 1 and 30 post-treatment. Chronic and subacute results were compared. RESULTS: Adverse events were rare, mild, and did not differ between groups. Language outcomes improved significantly in all groups irrespective of treatment and recovery phase. At 30-day follow-up, there was a significant interaction of stimulation and recovery phase on naming recovery (P <.001). Naming recovery with rTMS was larger in subacute (Mdn = 1.91/IQR = .77) than chronic patients (Mdn = .15/IQR = 1.68/P = .015). There was no significant rTMS effect in the chronic aphasia group. CONCLUSIONS: The addition of rTMS to SLT led to significant supplemental gains in naming recovery in the subacute phase only. While this needs confirmation in larger studies, our results clarify neuromodulatory vs training-induced effects and indicate a possible window of opportunity for contralesional inhibitory stimulation interventions in post-stroke aphasia. NORTHSTAR TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT02020421.

Observing symmetry-broken optimal paths of the stationary Kardar-Parisi-Zhang interface via a large-deviation sampling of directed polymers in random media.

Consider the short-time probability distribution P(H,t) of the one-point interface height difference h(x=0,τ=t)-h(x=0,τ=0)=H of the stationary interface h(x,τ) described by the Kardar-Parisi-Zhang (KPZ) equation. It was previously shown that the optimal path, the most probable history of the interface h(x,τ) which dominates the upper tail of P(H,t), is described by any of two ramplike structures of h(x,τ) traveling either to the left, or to the right. These two solutions emerge, at a critical value of H, via a spontaneous breaking of the mirror symmetry x↔-x of the optimal path, and this symmetry breaking is responsible for a second-order dynamical phase transition in the system. We simulate the interface configurations numerically by employing a large-deviation Monte Carlo sampling algorithm in conjunction with the mapping between the KPZ interface and the directed polymer in a random potential at high temperature. This allows us to observe the optimal paths, which determine each of the two tails of P(H,t), down to probability densities as small as 10^{-500}. At short times we observe mirror-symmetry-broken traveling optimal paths for the upper tail, and a single mirror-symmetric path for the lower tail, in good quantitative agreement with analytical predictions. At long times, even at moderate values of H, where the optimal fluctuation method is not supposed to apply, we still observe two well-defined dominating paths. Each of them violates the mirror symmetry x↔-x and is a mirror image of the other.

Phase transition for parameter learning of hidden Markov models.

We study a phase transition in parameter learning of hidden Markov models (HMMs). We do this by generating sequences of observed symbols from given discrete HMMs with uniformly distributed transition probabilities and a noise level encoded in the output probabilities. We apply the Baum-Welch (BW) algorithm, an expectation-maximization algorithm from the field of machine learning. By using the BW algorithm we then try to estimate the parameters of each investigated realization of an HMM. We study HMMs with n=4,8, and 16 states. By changing the amount of accessible learning data and the noise level, we observe a phase-transition-like change in the performance of the learning algorithm. For bigger HMMs and more learning data, the learning behavior improves tremendously below a certain threshold in the noise strength. For a noise level above the threshold, learning is not possible. Furthermore, we use an overlap parameter applied to the results of a maximum a posteriori (Viterbi) algorithm to investigate the accuracy of the hidden state estimation around the phase transition.

Impact of Lipoprotein(a) Levels on Perioperative Outcomes in Cardiac Surgery.

Altered lipid metabolism has been shown to be of major importance in a range of metabolic diseases, with particular importance in cardiovascular disease (CVD). As a key metabolic product, altered lipoprotein(a) (Lp(a)) levels may be associated with adverse clinical outcomes in high-risk cardiovascular patients undergoing cardiac surgery. We aimed to investigate the impact of the important metabolite Lp(a) on complications and clinical outcomes in high-risk patients. A prospective observational cohort study was performed. Data were derived from the Bern Perioperative Biobank (ClinicalTrials.gov NCT04767685), and included 192 adult patients undergoing elective cardiac surgery. Blood samples were collected at 24 h preoperatively, before induction of general anaesthesia, upon weaning from cardiopulmonary bypass (CPB), and the first morning after surgery. Clinical endpoints included stroke, myocardial infarction, and mortality within 30 days after surgery or within 1 year. Patients were grouped according to their preoperative Lp(a) levels: <30 mg/dL (n = 121; 63%) or >30 mg/dL (n = 71, 37%). The groups with increased vs. normal Lp(a) levels were comparable with regard to preoperative demographics and comorbidities. Median age was 67 years (interquartile range (IQR) 60.0, 73.0), with median body mass index (BMI) of 23.1 kg/m2 (23.7, 30.4), and the majority of patients being males (75.5%). Over the observational interval, Lp(a) levels decreased in all types of cardiac surgery after CPB (mean decline of approximately -5 mg/dL). While Lp(a) levels decreased in all patients following CPB, this observation was considerably pronounced in patients undergoing deep hypothermic circulatory arrest (DHCA) (decrease to preoperative Lp(a) levels by -35% (95% CI -68, -1.7), p = 0.039). Increased Lp(a) levels were neither associated with increased rates of perioperative stroke or major adverse events in patients undergoing cardiac surgery, nor with overall mortality in the perioperative period, or at one year after surgery. Other than for cohorts in neurology and cardiology, elevated Lp(a) might not be a risk factor for perioperative events in cardiac surgery.

Similarity of extremely rare nonequilibrium processes to equilibrium processes.

For system coupled to heat baths, typical nonequilibrated processes, e.g., induced by varying an external parameter without waiting for equilibration in between, are very different from the corresponding equilibrium infinitely slow processes. Nevertheless, there are connections between equilibrium and nonequilibrated behaviors, e.g., the theorems of Jarzynski and Crooks, which relate the distribution P(W) of nonequilibrium work to the free energy differences ΔF. Here we study the naturally arising question, whether those relevant but rare trajectories, which exhibit these work values, show a higher degree of similarity to equilibrium. For convenience, we have chosen a simple model of RNA secondary structures (or single-stranded DNA), here modeling a medium-size hairpin structure, under influence of a varying external force. This allows us to measure the work W during the resulting fast unfolding and refolding processes within Monte Carlo simulations, i.e., in nonequilibrium. Also we sample numerically efficiently directly in exact equilibrium, for comparison. Using a sophisticated large-deviation algorithm, we are able to measure work distributions with high precision down to probabilities as small as 10^{-46}, enabling us to verify the Crooks and Jarzynski theorems. Furthermore, we analyze force-extension curves and the configurations of the secondary structures during unfolding and refolding for typical equilibrium processes and nonequilibrated processes. We find that the nonequilibrated processes where the work values are close to those which are most relevant for applying Crooks and Jarzynski theorems, respectively, but which occur with exponential small probabilities, are most and quite similar to the equilibrium processes.

Effect of Perioperative Lipid Status on Clinical Outcomes after Cardiac Surgery.

Patients undergoing cardiac surgery are at increased cardiovascular risk, which includes altered lipid status. However, data on the effect of cardiac surgery and cardiopulmonary bypass (CPB) on plasma levels of key lipids are scarce. We investigated potential effects of CPB on plasma lipid levels and associations with early postoperative clinical outcomes. This is a prospective bio-bank study of patients undergoing elective cardiac surgery at our center January to December 2019. The follow-up period was 1 year after surgery. Blood sampling was performed before induction of general anesthesia, upon weaning from cardiopulmonary bypass (CPB), and on the first day after surgery. Clinical end points included the incidence of postoperative stroke, myocardial infarction, and death of any cause at 30 days after surgery as well as 1-year all-cause mortality. A total of 192 cardiac surgery patients (75% male, median age 67.0 years (interquartile range 60.0-73.0), median BMI 26.1 kg/m2 (23.7-30.4)) were included. A significant intraoperative decrease in plasma levels compared with preoperative levels (all p < 0.0001) was observed for total cholesterol (TC) (Cliff's delta d: 0.75 (0.68-0.82; 95% CI)), LDL-Cholesterol (LDL-C) (d: 0.66 (0.57-0.73)) and HDL-Cholesterol (HDL-C) (d: 0.72 (0.64-0.79)). At 24h after surgery, the plasma levels of LDL-C (d: 0.73 (0.650.79)) and TC (d: 0.77 (0.69-0.82)) continued to decrease compared to preoperative levels, while the plasma levels of HDL-C (d: 0.46 (0.36-0.55)) and TG (d: 0.40 (0.29-0.50)) rebounded, but all remained below the preoperative levels (p < 0.001). Mortality at 30 days was 1.0% (N = 2/192), and 1-year mortality was 3.8% (N = 7/186). Postoperative myocardial infarction occurred in 3.1% of patients (N = 6/192) and postoperative stroke in 5.8% (N = 11/190). Adjusting for age, sex, BMI, and statin therapy, we noted a protective effect of postoperative occurrence of stroke for pre-to-post-operative changes in TC (adjusted odds ratio (OR) 0.29 (0.07-0.90), p = 0.047), in LDL-C (aOR 0.19 (0.03-0.88), p = 0.045), and in HDL-C (aOR 0.01 (0.00-0.78), p = 0.039). No associations were observed between lipid levels and 1-year mortality. In conclusion, cardiac surgery induces a significant sudden drop in levels of key plasma lipids. This effect was pronounced during the operation, and levels remained significantly lowered at 24 h after surgery. The intraoperative drops in LDL-C, TC, and HDL-C were associated with a protective effect against occurrence of postoperative stroke in adjusted models. We demonstrate that the changes in key plasma lipid levels during surgery are strongly correlated, which makes attributing the impact of each lipid to the clinical end points, such as postoperative stroke, a challenging task. Large-scale analyses should investigate additional clinical outcome measures.

Ranking Biomarkers of Aging by Citation Profiling and Effort Scoring.

Aging affects most living organisms and includes the processes that reduce health and survival. The chronological and the biological age of individuals can differ remarkably, and there is a lack of reliable biomarkers to monitor the consequences of aging. In this review we give an overview of commonly mentioned and frequently used potential aging-related biomarkers. We were interested in biomarkers of aging in general and in biomarkers related to cellular senescence in particular. To answer the question whether a biological feature is relevant as a potential biomarker of aging or senescence in the scientific community we used the PICO strategy known from evidence-based medicine. We introduced two scoring systems, aimed at reflecting biomarker relevance and measurement effort, which can be used to support study designs in both clinical and research settings.