Discrete Populations Research Articles

DUAL PET IMAGING OF NEOPLASTIC AND INflAMMATORY BIOMARKERS IN HIGH GRADE GLIOMA

Abstract AIMS To characterize spatial distributions of 18kDa translocator protein (TSPO) and amino acid uptake as measured through dynamic [11C] (R)-PK11195 and [11C]-methionine PET in high-grade glioma. METHOD Twelve patients with newly diagnosed high-grade glioma underwent dual PET studies. [11C] (R)-PK11195 binding potential (BPND) maps were generated using simplified reference tissue model with grey-matter cerebellar time- activity-curve as tissue input-function. [11C]-methionine uptake was calculated as tumour-to-background ratio (TBR). Volumes of interest (VOIs) were defined on T1W post-contrast MRI as contrast-enhancing (CE) tumour and a ‘peritumoural’ region 5mm from the CE edge. Voxel-wise comparison of the tracers used Pearson’s correlation coeffcient. VOIs were furthermore subdivided into higher/lower TSPO (BPND > 0.17) and higher/lower methionine (TBR > 1.7). RESULTS Within the CE, voxel-wise comparison showed a strong correlation (r > 0.7) in eight subjects, moderate correlation (r > 0.5) in three subjects and weak correlation (r < 0.5) in one subject. Volume (mm3) with high BPND/high TBR accounted for 62±29% whereas high BPND/low TBR accounted for 13±16%. Within the peritumoral area, there was a small reduction in the proportion of subjects in the strong correlation group (6/12) but the pro- portion of voxels with higher TSPO binding and lower methionine uptake was substantially greater (35±16%). CONCLUSIONS Within high-grade glioma, there is a strong overall correlation between TSPO expression and amino acid uptake. However, in the peritumoural region there are areas of elevated TSPO expression without increased methionine uptake which could represent an inflammatory component or a discrete neoplastic cell population that may not be adequately defined with standard imaging biomarkers.

Technique to derive discrete population models with delayed growth

We provide a procedure for deriving discrete population models for the size of the adult population at the beginning of each breeding cycle and assume only adult individuals reproduce. This derivation technique includes delay to account for the number of breeding cycles that a newborn individual remains immature and does not contribute to reproduction. These models include a survival probability (during the delay period) for the immature individuals, since these individuals have to survive to reach maturity and become members of, what we consider, the adult population. We discuss properties of this class of discrete delay population models and show that there is a critical delay threshold. The population goes extinct if the delay exceeds this threshold. We apply this derivation procedure to obtain two models, a Beverton–Holt adult model and a Ricker adult model and discuss the global dynamics of both models.

Quantification of prefrontal cortical neuronal ensembles following conditioned fear learning in a Fos-LacZ transgenic rat with photoacoustic imaging in Vivo

Understanding the neurobiology of complex behaviors requires measurement of activity in the discrete population of active neurons, neuronal ensembles, which control the behavior. Conventional neuroimaging techniques ineffectively measure neuronal ensemble activity in the brain in vivo because they assess the average regional neuronal activity instead of the specific activity of the neuronal ensemble that mediates the behavior. Our functional molecular photoacoustic tomography (FM-PAT) system allows direct imaging of Fos-dependent neuronal ensemble activation in Fos-LacZ transgenic rats in vivo. We tested four experimental conditions and found increased FM-PAT signal in prefrontal cortical areas in rats undergoing conditioned fear or novel context exposure. A parallel immunofluorescence ex vivo study of Fos expression found similar findings. These findings demonstrate the ability of FM-PAT to measure Fos-expressing neuronal ensembles directly in vivo and support a mechanistic role for the prefrontal cortex in higher-order processing of response to specific stimuli or environmental cues.

Orexin and MCH neurons: regulators of sleep and metabolism.

Sleep-wake and fasting-feeding are tightly coupled behavioral states that require coordination between several brain regions. The mammalian lateral hypothalamus (LH) is a functionally and anatomically complex brain region harboring heterogeneous cell populations that regulate sleep, feeding, and energy metabolism. Significant attempts were made to understand the cellular and circuit bases of LH actions. Rapid advancements in genetic and electrophysiological manipulation help to understand the role of discrete LH cell populations. The opposing action of LH orexin/hypocretin and melanin-concentrating hormone (MCH) neurons on metabolic sensing and sleep-wake regulation make them the candidate to explore in detail. This review surveys the molecular, genetic, and neuronal components of orexin and MCH signaling in the regulation of sleep and metabolism.

Abstract P1021: Estimating Cardiac Cell Composition In Gtex With Single-nucleus Reference Profiles.

Heart failure (HF) is a heterogeneous condition defined by an inability of the heart to meet the circulatory needs of the body. HF is the result of a maladaptive response to chronic stressors during which the heart undergoes structural and cellular remodeling. For example, cardiomyocytes undergo apoptosis after chronic overstimulation while fibroblasts proliferate to fill gaps left by the loss of larger cells. Although changes to the cellular makeup of the heart are known to mediate HF pathology, estimates of basal cardiac cellular composition vary widely. Moreover, despite our understanding of HF as a complex condition that is influenced by environmental and genetic factors, most studies on heart composition only examine small groups of individuals or inbred models. Recent efforts have used single-nucleus RNAseq (snRNAseq) to tally nuclear proportions as a proxy for cellular proportions. However, cellular dissociation biases for certain cell types and skews the resulting estimates. Furthermore, snRNAseq studies are expensive, making them infeasible and underpowered for population-scale analyses. To avoid these issues, we developed a method to estimate cellular composition of bulk RNAseq using cell-type-specific references defined in snRNAseq. While most deconvolution tools are designed for single-cell RNAseq inputs, our method considers the technical and biological differences of snRNAseq. It also allows for the inclusion of additional reference datasets, utilizes simulated controls, and leverages an existing deconvolution tool, MuSiC. We apply our method to the Genome-Tissue-Expression project (GTEx), a multi-tissue database with bulk RNAseq from hundreds of subjects and snRNAseq from a small subset of those subjects. We estimated left ventricular cellular composition in 386 individuals, revealing considerable heterogeneity. We found significant correlations between subject phenotypes and discrete cell populations. This analysis demonstrates our ability to leverage existing, public datasets to accurately map the understudied variability of cardiac cell type variation across human populations. We now look to incorporate genomic datasets to find genetic markers that link composition estimates to population-level variation.

Stationary status of discrete and continuous age-structured population models

From Leonhard Euler to Alfred Lotka and in recent years understanding the stationary process of the human population has been of central interest to scientists. Population reproductive measure NRR (net reproductive rate) has been widely associated with measuring the status of population stationarity and it is also included as one of the measures in the millennium development goals. This article argues how the partition theorem-based approach provides more up-to-date and timely measures to find the status of the population stationarity of a country better than the NRR-based approach. We question the timeliness of the value of NRR in deciding the stationary process of the country. We prove associated theorems on discrete and continuous age distributions and derive measurable functional properties. The partitioning metric captures the underlying age structure dynamic of populations at or near stationarity. As the population growth rates for an ever-increasing number of countries trend towards replacement levels and below, new demographic concepts and metrics are needed to better characterize this emerging global demography.

Juvenile proportion as a predictor of freshwater turtle population change

AbstractThe extreme longevity of turtles and tortoises can make it difficult to determine the conservation status of their populations because high annual adult survival may mask gradual attrition due to low levels of recruitment. When long‐term demographic trends are unknown and available data are insufficient for population modelling, it may be assumed that a scarcity of juveniles indicates low recruitment that will result in population ageing and numerical decline. However, the reliability with which the proportion of juveniles foreshadows demographic change is uncertain. We tested the hypothesis that a low proportion of juveniles in a turtle population presages its ageing by analysing over 20 years of survey data for five discrete populations of the Australian western saw‐shelled turtle (Myuchelys bellii: Chelidae), a listed threatened species. The analysis tested whether the initial proportion of juvenile turtles in each population was related to its temporal trend in average body size. The five populations had varied structure and trends, with the initial proportion of juvenile turtles ranging from 10% to 39% and average body size increasing over time in some populations and decreasing in others. Contrary to expectation, the initial proportion of juveniles was unrelated to the trend in average body size and, by inference, average age, indicating that effective trend forecasting requires more detailed demographic information than merely population structure.

Loss of normal Alzheimer's disease-associated Presenilin 2 function alters antiseizure medicine potency and tolerability in the 6-Hz focal seizure model.

Patients with early-onset Alzheimer's disease (EOAD) experience seizures and subclinical epileptiform activity, which may accelerate cognitive and functional decline. Antiseizure medicines (ASMs) may be a tractable disease-modifying strategy; numerous ASMs are marketed with well-established safety. However, little information is available to guide ASM selection as few studies have rigorously quantified ASM potency and tolerability in traditional seizure models in rodents with EOAD-associated risk factors. Presenilin 2 (PSEN2) variants evoke EOAD, and these patients experience seizures. This study thus established the anticonvulsant profile of mechanistically distinct ASMs in the frontline 6-Hz limbic seizure test evoked in PSEN2-knockout (KO) mice to better inform seizure management in EOAD. The median effective dose (ED50) of prototype ASMs was quantified in the 6-Hz test in male and female PSEN2-KO and wild-type (WT) C57BL/6J mice (3-4 months old). Minimal motor impairment (MMI) was assessed to estimate a protective index (PI). Immunohistological detection of cFos established the extent to which 6-Hz stimulation activates discrete brain regions in KO vs. WT mice. There were significant genotype-related differences in the potency and tolerability of several ASMs. Valproic acid and levetiracetam were significantly more potent in male KO than in WT mice. Additionally, high doses of valproic acid significantly worsened MMI in KO mice. Conversely, carbamazepine was significantly less potent in female KO vs. WT mice. In both male and female KO mice vs. WTs, perampanel and lamotrigine were equally potent. However, there were marked genotype-related shifts in PI of both carbamazepine and perampanel, with KO mice exhibiting less MMI at the highest doses tested. Gabapentin was ineffective against 6-Hz seizures in KO mice vs. WTs without MMI changes. Neuronal activation 90 min following 6-Hz stimulation was significantly increased in the posterior parietal association cortex overlying CA1 and in the piriform cortex of WT mice, while stimulation-induced increases in cFos immunoreactivity were absent in KO mice. Acute ASM potency and tolerability in the high-throughput 6-Hz test may be significantly altered with loss of normal PSEN2 function. Seizures in discrete EOAD populations may benefit from precisely selected medicines optimized for primary ASM pharmacological mechanisms.

Obesity wars: hypothalamic sEVs a new hope.

There are currently several pharmacological therapies available for the treatment of obesity, targeting both the central nervous system (CNS) and peripheral tissues. In recent years, small extracellular vesicles (sEVs) have been shown to be involved in many pathophysiological conditions. Because of their special nanosized structure and contents, sEVs can activate receptors and trigger intracellular pathways in recipient cells. Notably, in addition to transferring molecules between cells, sEVs can also alter their phenotypic characteristics. The purpose of this review is to discuss how sEVs can be used as a CNS-targeted strategy for treating obesity. Furthermore, we will evaluate current findings, such as the sEV-mediated targeting of hypothalamic AMP-activated protein kinase (AMPK), and discuss how they can be translated into clinical application.

Surgical Site Infections During the Pandemic: The Impact of the "COVID Bundle".

A reduction in surgical site infections (SSIs) has been reported in several discrete patient populations during the COVID-19 pandemic. Herein, this study evaluates the impact of the COVID-19 pandemic on SSI in a large patient cohort incorporating multiple surgical disciplines. We hypothesize that enhanced infection control and heightened awareness of such measures is analogous to an SSI care bundle, the hypothetical "COVID bundle", and may impact SSI rates. Data collected for the American College of Surgeons National Surgical Quality Improvement Program between January 1, 2015, and April 1, 2021, were retrospectively analyzed. SSI rates were compared among time-dependent patient cohorts: Cohort A (pre-pandemic, N = 24,060, 87%) and Cohort B (pandemic, N = 3698, 13%). Time series and multivariable analyses predicted pre-pandemic and pandemic SSI trends and tested for association with timing of surgery. The overall SSI incidence was reduced in Cohort B versus Cohort A (2.8% vs. 4.5%, p < 0.001). Multivariable analysis indicated a downward SSI trend before pandemic onset (IRR 0.997, 95% CI 0.994, 1). At pandemic onset, the trend reduced by a relative factor of 39% (IRR 0.601, 95% CI 0.338, 1.069). SSI then trended upward during the pandemic (IRR 1.035, 95% CI 0.965, 1.111). SSI rates significantly trended downward in general surgical patients at pandemic onset (IRR 0.572, 95% CI 0.353, 0.928). Although overall SSI incidence was reduced during the pandemic, a statistically significant decrease in the predicted SSI rate only occurred in general surgical patients at pandemic onset. This trend may suggest a positive impact of the "COVID bundle" on SSI rates in these patients.

Multiple origins define the genetic structure of tiger shrimp Penaeus monodon in the colombian Caribbean Sea

The tiger shrimp Penaeus monodon is a native species of the Indo-Pacific Ocean that was introduced to promote its cultivation in several American countries, including Colombia. As a result of inappropriate aquaculture practices, it has established itself in the wild in almost all the Colombian Caribbean Sea. To evaluate the genetic diversity, population structure, and origin of the founder populations, samples from three sites in the Colombian Caribbean were analyzed from 10 microsatellite loci and the mitochondrial DNA Control Region. Genetic diversity similar to native populations was found to be present in three relatively discrete populations and their origin is related to natural populations from Thailand, the Philippines, Taiwan and China. We discuss how oceanographic conditions and culture systems of tiger shrimp facilitated the success of biological invasion processes in marine ecosystems of the Colombian Caribbean.

Coastal upwelling influences population structure of dusky grouper Epinephelus marginatus: An integrative approach based on otolith chemistry and muscle stable isotopes

The dusky grouper (Epinephelus marginatus) is an overfished and threatened fish species with coastal distribution. In the Southwestern Atlantic, it occurs across a broad region influenced by two major oceanographic features: the Cabo Frio (23°S) and the Cabo Santa Marta (28°S) upwelling systems. Along the Brazilian coast, the species may present continuous or discrete populations, depending on the methodological approach used. In this study we combined otolith chemistry and muscle stable isotope analyses to examine the population structure of dusky groupers and its association with the two upwelling systems. Fish were collected in shallow coastal waters of the Southwest Atlantic Ocean, covering the southeastern and southern Brazilian coasts, among Macaé (22°S), Santos (24°S), Florianópolis (27°S), and in Rio Grande (32°S). The results show three statistically well-separated population groups along the region. We named these population groups as North (north of Cabo Frio); Center (between upwelling regions); and South (south of the Cabo Santa Marta system). Our findings allow to suggest that the upwelling systems may influence the distribution of E. marginatus stocks along the Brazilian south-western coast, even though a causal effect may not be attributed at this point. Overall, this combined approach, leveraging information from distinct natural tags, and reflecting variability of water chemistry and food webs with latitude, allowed us to enhance our understanding on how major upwelling systems influence the structuring of fish populations along the southwestern Atlantic Ocean.

GluCl.Cre ON enables selective inhibition of molecularly defined pain circuits.

Insight into nociceptive circuits will ultimately build our understanding of pain processing and aid the development of analgesic strategies. Neural circuit analysis has been advanced greatly by the development of optogenetic and chemogenetic tools, which have allowed function to be ascribed to discrete neuronal populations. Neurons of the dorsal root ganglion, which include nociceptors, have proved challenging targets for chemogenetic manipulation given specific confounds with commonly used DREADD technology. We have developed a cre/lox dependant version of the engineered glutamate-gated chloride channel (GluCl) to restrict and direct its expression to molecularly defined neuronal populations. We have generated GluCl.Cre ON that selectively renders neurons expressing cre-recombinase susceptible to agonist-induced silencing. We have functionally validated our tool in multiple systems in vitro, and subsequently generated viral vectors and tested its applicability in vivo. Using Nav1.8 Cre mice to restrict AAV-GluCl.Cre ON to nociceptors, we demonstrate effective silencing of electrical activity in vivo and concomitant hyposensitivity to noxious thermal and noxious mechanical pain, whereas light touch and motor function remained intact. We also demonstrated that our strategy can effectively silence inflammatory-like pain in a chemical pain model. Collectively, we have generated a novel tool that can be used to selectively silence defined neuronal circuits in vitro and in vivo. We believe that this addition to the chemogenetic tool box will facilitate further understanding of pain circuits and guide future therapeutic development.

Looking for Parasites as Potential Biological Tags for Pacific Thread Herring, Opisthonema libertate (Günther, 1867) (Clupeiformes, Dorosomatidae), in the Gulf of California

The Pacific thread herring, Opisthonema libertate, is a fishery resource in the eastern tropical Pacific, yet its population dynamics are poorly understood. The aims of this work were to document the metazoan parasite species in O. libertate from the Gulf of California in Mexico, determine latitudinal changes in their infection levels, and assess their potential as biological tags. Six parasitic species were identified: Myosaccium ecaude and Parahemiurus merus digeneans, Cribromazocraes cf. travassosi and Mazocraeoides georgei monogeneans, Pseudoterranova sp. nematodes, and Lepeophtheirus sp. copepods. The monogenean and copepod species are reported for the first time in O. libertate. Many fish were infected with digeneans, and there was a rare occurrence of other parasites. While the prevalence and median intensity of M. ecaude and P. merus significantly varied among sampling localities, a multivariate analysis revealed a distinct separation between some localities; these results suggest that individual fish form several discrete populations. However, the utility of these parasites as biological tags will be further probed because they cannot satisfy all requirements for good biological tags. The present results might be helpful in complementing other techniques to determine the movement and stock structure of O. libertate, albeit with certain limitations.

Dynamical behaviour of discrete logistic equation with Allee effect in an uncertain environment

The Allee effect refers to a natural occurrence where the average individual fitness of a population or species is correlated with population size or density. A demographic Allee effect having a threshold population size constitutes a strong Allee effect. On the contrary, it is called the weak Allee effect when it lacks an adequate population size. This paper revisits a single-species logistic growth model under the combined impacts of the strong Allee effect, discrete population dynamics, and an impreciseness phenomenon. Several existing literatures on models with deterministic and continuous time frames address the Allee effect’s significance. The population growth model may disobey the continuous time frame of dynamics. The difference equation may be a fruitful substitute for the traditional differential equation to trace a discrete logistic population growth model phenomenon. Also, initial information and the population growth model’s associated coefficient may sometimes be vague. Fuzzy logic is a suitable tool to describe such vagueness in mathematical terms. We have discussed the proposed model through the different fuzzy scenarios to realize the relative impact of different fuzzy parameters. This paper also includes the studies of equilibrium points and their corresponding stability analysis for each case. This paper differs from the existing literature on Allee effect in that it contributes an alternative approach to manifest the logistic growth model in a discrete time frame under uncertainty. Numerical results show the fuzzy impact of different parameters of the model. One of the significant insights of the outcome is that the extinction or highly growing population depends on the parameter’s values rather than the population size only.

VITAL RATES, THEIR VARIATION AND NATURAL SELECTION: A CASE FOR AN ATLANTIC FOREST MARSUPIAL

Evolutionary theory predicts that viable wild populations confront environmental variation by maintaining the variance of the most important vital rates low, a phenomenon also known as demographic buffering. However, patterns diverging from the demographic buffering hypothesis have also been reported. Here we used Population Matrix Models to test the hypothesis of buffering in the early survival of an Atlantic Forest marsupial. We used sensitivity analyses, which allow quantifying the effects that perturbations in specific vital rates could have on the population’s growth rate. We obtained the sensitivities, elasticities, and second-order derivatives of the discrete population growth rate with respect to different vital rates for a population of the black-eared opossum ( Didelphis aurita , Marsupialia, Didelphidae) in a preserved Atlantic Forest, the state of Rio de Janeiro, Brazil. The second-order derivatives offer an insight into the selection forces occurring during the life cycle, clarifying the processes behind the common pattern of early-survival importance. We found evidence of buffering in early survival, however, in one of the cohorts, early survival displayed evidence of opposed behavior to the expected under demographic buffering, thus revealing that established life-history patterns can be quickly modified by a small change in one vital rate.

Theoretical analysis of a discrete population balance model with sum kernel

The Oort–Hulst–Safronov equation is a relevant population balance model. Its discrete form, developed by Pavel Dubovski, is the main focus of our analysis. The existence and density conservation are established for non-negative symmetric coagulation rates satisfying V_{i,j} \leqslant i+j , \forall i,j \in \mathbb{N} . Differentiability of the solutions is investigated for kernels with V_{i,j} \leqslant i^{\alpha}+j^{\alpha} where 0 \leqslant \alpha \leqslant 1 with initial conditions with bounded (1+\alpha) -th moments. The article ends with a uniqueness result under an additional assumption on the coagulation kernel and the boundedness of the second moment.

COMPARISON OF RESULTS OF NUMERICAL ANALYSIS OF SIMULATION OF CYBERPHYSICAL BIOSENSOR SYSTEMS

The article compares the results of numerical modeling of mathematical models of cyber-physical biosensor systems using lattice difference equations with time delay on hexagonal and rectangular lattices. The main attention is paid to the mathematical description of the dynamics of a discrete population in combination with the dynamic logic of the studied models. Lattice difference equations with delay are proposed for modeling the antigen-antibody interaction in hexagonal and rectangular biopixels. Similar to the diffusion phenomenon, spatial operators are considered to model the interaction between biopixels. The paper compares the results of numerical modeling of processes occurring in biopixels of cyberphysical biosensor systems in the form of phase plane images and lattice images of the probability of antigen-antibody bonds. Based on the obtained experimental results, a comparative analysis of the stability of mathematical models was carried out using lattice difference equations on hexagonal and rectangular lattices for cyberphysical biosensors.

Conformational ensembles explain NMR spectra of frozen intrinsically disordered proteins.

Protein regions which are intrinsically disordered, exist as an ensemble of rapidly interconverting structures. Cooling proteins to cryogenic temperatures for dynamic nuclear polarization (DNP) magic angle spinning (MAS) NMR studies suspends most of the motions, resulting in peaks that are broad but not featureless. To demonstrate that detailed conformational restraints can be retrieved from the peak shapes of frozen proteins alone, we developed and used a simulation framework to assign peak features to conformers in the ensemble. We validated our simulations by comparing them to spectra of α-synuclein acquired under different experimental conditions. Our assignments of peaks to discrete dihedral angle populations suggest that structural constraints are attainable under cryogenic conditions. The ability to infer ensemble populations from peak shapes has important implications for DNP MAS NMR studies of proteins with regions of disorder in living cells because chemical shifts are the most accessible measured parameter.

Integrated systems immunology approach identifies impaired effector T cell memory responses as a feature of progression to severe dengue fever

BackgroundTypical symptoms of uncomplicated dengue fever (DF) include headache, muscle pains, rash, cough, and vomiting. A proportion of cases progress to severe dengue hemorrhagic fever (DHF), associated with increased vascular permeability, thrombocytopenia, and hemorrhages. Progression to severe dengue is difficult to diagnose at the onset of fever, which complicates patient triage, posing a socio-economic burden on health systems.MethodsTo identify parameters associated with protection and susceptibility to DHF, we pursued a systems immunology approach integrating plasma chemokine profiling, high-dimensional mass cytometry and peripheral blood mononuclear cell (PBMC) transcriptomic analysis at the onset of fever in a prospective study conducted in Indonesia.ResultsAfter a secondary infection, progression to uncomplicated dengue featured transcriptional profiles associated with increased cell proliferation and metabolism, and an expansion of ICOS+CD4+ and CD8+ effector memory T cells. These responses were virtually absent in cases progressing to severe DHF, that instead mounted an innate-like response, characterised by inflammatory transcriptional profiles, high circulating levels of inflammatory chemokines and with high frequencies of CD4low non-classical monocytes predicting increased odds of severe disease.ConclusionsOur results suggests that effector memory T cell activation might play an important role ameliorating severe disease symptoms during a secondary dengue infection, and in the absence of that response, a strong innate inflammatory response is required to control viral replication. Our research also identified discrete cell populations predicting increased odds of severe disease, with potential diagnostic value.