Modeling of the Time-Dependent H2 Emission and Equilibrium Time in H2-Enriched Polymers with Cylindrical, Spherical and Sheet Shapes and Comparisons with Experimental Investigations.

Time-dependent emitted H2 content modeling via a reliable diffusion analysis program was performed for H2-enriched polymers under high pressure. Here, the emitted hydrogen concentration versus elapsed time was obtained at different diffusivities and volume dimensions for cylinder-, sphere- and sheet-shaped specimens. The desorption equilibrium time, defined as the time when the H2 emission content is nearly saturated, was an essential factor for determining the periodic cyclic testing and high-pressure H2 exposure effect. The equilibrium time in the desorption process was modeled. The equilibrium time revealed an exponential growth behavior with respect to the squared thickness and the squared diameter of the cylinder--shaped specimen, while it was proportional to the squared diameter for the sphere-shaped specimen and to the squared thickness for the sheet-shaped specimen. Linear relationships between the reciprocal equilibrium time and diffusivity were found for all shaped polymers. The modeling results were confirmed by analysis of the solutions using Fick's second diffusion law and were consistent with the experimental investigations. Numerical modeling provides a useful tool for predicting the time-dependent emitted H2 behavior and desorption equilibrium time. With a known diffusivity, a complicated time-dependent emitted H2 behavior with a multi-exponential form of an infinite series could also be predicted for the three shaped samples using a diffusion analysis program.

Influence of selection on the probability of fixation at a locus with multiple alleles.

BACKGROUND: Genes exist in a population in a variety of forms (alleles), as a consequence of multiple mutation events that have arisen over the course of time. In this work we consider a locus that is subject to either multiplicative or additive selection, and has n alleles, where n can take the values 2, 3, 4, … . We focus on determining the probability of fixation of each of the n alleles. For n = 2 alleles, analytical results, that are 'exact', under the diffusion approximation, can be found for the fixation probability. However generally there are no equally exact results for n ≥ 3 alleles. In the absence of such exact results, we proceed by finding results for the fixation probability, under the diffusion approximation, as a power series in scaled strengths of selection such as R i , j = 2 N e ( s i - s j ) , where N e is the effective population size, while s i and s j are the selection coefficients associated with alleles i and j, respectively. RESULTS: We determined the fixation probability when all terms up to second order in the R i , j are kept. The truncation of the power series requires that the R i , j cannot be indefinitely large. For magnitudes of the R i , j up to a value of approximately 1, numerical evidence suggests that the results work well. Additionally, results given for the particular case of n = 3 alleles illustrate a general feature that holds for n ≥ 3 alleles, that the fixation probability of a particular allele depends on that allele's initial frequency, but generally, this fixation probability also depends on the initial frequencies of other alleles at the locus, as well as their selective effects. CONCLUSIONS: We have analytically exposed the leading way the probability of fixation, at a locus with multiple alleles, is affected by selection. This result may offer important insights into CDCV traits that have extreme phenotypic variance due to numerous, low-penetrance susceptibility alleles.

Coupled information networks drive honeybee (Apis mellifera) collective foraging.

Collective behaviour by eusocial insect colonies is typically achieved through multiple communication networks that produce complex behaviour at the group level but often appear to provide redundant or even competing information. A classic example occurs in honeybee (Apis mellifera) colonies, where both the dance communication system and robust scent-based mechanisms contribute to the allocation of a colony's workforce by regulating the flow of experienced foragers among known food sources. Here we analysed social connectivity patterns during the reactivation of experienced foragers to familiar feeding sites to show that these social information pathways are not simply multiple means to achieve the same end but intersect to play complementary roles in guiding forager behaviour. Using artificial feeding stations, we mimicked a natural scenario in which two forager groups were simultaneously collecting from distinct patches containing different flowering species. We then observed the reactivation of these groups at their familiar feeding sites after interrupting their foraging. Social network analysis revealed that temporarily unemployed individuals interacted more often and for longer with foragers that advertised a familiar versus unfamiliar foraging site. Due to such resource-based assortative mixing, network-based diffusion analysis estimated that reactivation events primarily resulted from interactions among bees that had been trained to the same feeding station and less so from different-feeder interactions. Both scent- and dance-based interactions strongly contributed to reactivation decisions. However, each bout of dance-following had an especially strong effect on a follower's likelihood of reactivation, particularly when dances indicated locations familiar to followers. Our findings illustrate how honeybee foragers can alter their social connectivity in ways that are likely to enhance collective outcomes by enabling foragers to rapidly access up-to-date information about familiar foraging sites. In addition, our results highlight how reliance on multiple communication mechanisms enables social insect workers to utilise flexible information-use strategies that are robust to variation in the availability of social information.

Three-compartment spectral diffusion analysis for breast cancer magnetic resonance imaging.

RATIONALE AND OBJECTIVES: To examine the diagnostic performance of a three-compartment diffusion model with the fixed cut-off diffusion coefficient (D) using magnetic resonance spectral diffusion analysis for differentiating between invasive ductal carcinoma (IDC) and ductal carcinoma in situ (DCIS) and compare the conventional apparent D (ADC), and mean kurtosis (MK), with the tissue D (DIVIM), perfusion D (D*IVIM), and perfusion fraction (fIVIM) calculated by conventional intravoxel incoherent motion. PATIENTS AND METHODS: This retrospective study included women who underwent breast MRI with eight b-value diffusion-weighted imaging between February 2019 and March 2022. Spectral diffusion analysis was performed; very-slow, cellular, and perfusion compartments were defined using cut-off Ds of 0.1 × 10-3 and 3.0 × 10-3 mm2/s (static water D). The mean D (Ds, Dc, Dp, respectively) and fraction F (Fs, Fc, Fp, respectively) for each compartment were calculated. ADC and MK values were also calculated; receiver operating characteristic analyses were performed. RESULTS: Histologically confirmed 132 ICD and 62 DCIS (age range 31-87 [53 ± 11] years) were evaluated. The areas under the curve (AUCs) for ADC, MK, DIVIM, D*IVIM, fIVIM, Ds, Dc, Dp, Fs, Fc, and Fp were 0.77, 0.72, 0.77, 0.51, 0.67, 0.54, 0.78, 0.51, 0.57, 0.54, and 0.57, respectively. The AUCs for the model combining very-slow and cellular compartments and the model combining the three compartments were 0.81 each, slightly and significantly higher than for ADC, DIVIM, and Dc (P = 0.09-0.14); and MK (P < 0.05), respectively. CONCLUSION: Three-compartment model analysis using the diffusion spectrum accurately differentiated IDC from DCIS; however, it was not superior to ADC and DIVIM. The diagnostic performance of MK was lower than that of the three-compartment model.

Analysis of plant cuticles and their interactions with agrochemical surfactants using a 3D printed diffusion chamber.

BACKGROUND: Decades of research is available on their effects of single component surfactant on active ingredient diffusion across plant cuticular membranes, but ingredient diffusion is rarely analysed in the presence of commercial surfactants. Also, diffusion studies require expensive or specialized apparatus the  fabrication of which often requires skilled labour and specialized facilities. In this research we have addressed both problems where the effects of four commercially available surfactants on a known tracer molecule were investigated using a 3D printed customized diffusion chamber. RESULTS: As a proof-of-concept a customized 3D printed diffusion chamber was devised using two different thermoplastics and was successfully used in a range of diffusion tests . The effect of various solvents and surfactants on S. lycopersicum cuticular membrane indicated an increased rate of flux of tracer molecules across the membranes. This research has validated the application of 3D printing in diffusion sciences and demonstrated the flexibility and potential of this technique. CONCLUSIONS: Using a 3D printed diffusion apparatus, the effect of commercial surfactants on molecular diffusion through isolated plant membranes was studied. Further, we have included  here the steps involved in material selection, design, fabrication, and post processing procedures for successful recreation of the chamber. The customizability and rapid production process of the 3D printing demonstrates the power of additive manufacturing in the design and use of customizable labware.

Measuring the Co-Localization and Dynamics of Mobile Proteins in Live Cells Undergoing Signaling Responses.

Single molecule imaging in live cells enables the study of protein interactions and dynamics as they participate in signaling processes. When combined with fluorophores that stochastically transition between fluorescent and reversible dark states, as in super-resolution localization imaging, labeled molecules can be visualized in single cells over time. This improvement in sampling enables the study of extended cellular responses at the resolution of single molecule localization. This chapter provides optimized experimental and analytical methods used to quantify protein interactions and dynamics within the membranes of adhered live cells. Importantly, the use of pair-correlation functions resolved in both space and time allows researchers to probe interactions between proteins on biologically relevant distance and timescales, even though fluorescence localization methods typically require long times to assemble well-sampled reconstructed images. We describe an application of this approach to measure protein interactions in B cell receptor signaling and include sample analysis code for post-processing of imaging data. These methods are quantitative, sensitive, and broadly applicable to a range of signaling systems.

Social behaviour and transmission of lameness in a flock of ewes and lambs.

Introduction: Sheep have heterogenous social connections that influence transmission of some infectious diseases. Footrot is one of the top five globally important diseases of sheep, it is caused by Dichelobacter nodosus and transmits between sheep when infectious feet contaminate surfaces, e.g., pasture. Surfaces remain infectious for a few minutes to a few days, depending on surface moisture levels. Susceptible sheep in close social contact with infectious sheep might be at risk of becoming infected because they are likely to step onto infectious footprints, particularly dams and lambs, as they cluster together. Methods: High resolution proximity sensors were deployed on 40 ewes and their 54 lambs aged 5-27 days, in a flock with endemic footrot in Devon, UK for 13 days. Sheep locomotion was scored daily by using a 0-6 integer scale. Sheep were defined lame when their locomotion score (LS) was ≥2, and a case of lameness was defined as LS ≥2 for ≥2 days. Results: Thirty-two sheep (19 ewes, 9 single, and 4 twin lambs) became lame during the study, while 14 (5 ewes, 5 single, and 4 twin lambs) were lame initially. These 46 sheep were from 29 family groups, 14 families had >1 lame sheep, and transmission from ewes to lambs was bidirectional. At least 15% of new cases of footrot were from within family transmission; the occurrence of lameness was higher in single than twin lambs. At least 4% of transmission was due to close contact across the flock. Most close contact occurred within families. Single and twin lambs spent 1.5 and 0.9 hours/day with their dams, respectively, and twin lambs spent 3.7 hours/day together. Non-family sheep spent only 0.03 hours/day in contact. Lame single lambs and ewes spent less time with non-family sheep, and lame twin lambs spent less time with family sheep. Discussion: We conclude that most transmission of lameness is not attributable to close contact. However, in ewes with young lambs, some transmission occurs within families and is likely due to time spent in close contact, since single lambs spent more time with their dam than twin lambs and were more likely to become lame.

Cultural diffusion dynamics depend on behavioural production rules.

Culture is an outcome of both the acquisition of knowledge about behaviour through social transmission, and its subsequent production by individuals. Acquisition and production are often discussed or modelled interchangeably, yet to date no study has explored the consequences of their interaction for cultural diffusions. We present a generative model that integrates the two, and ask how variation in production rules might influence diffusion dynamics. Agents make behavioural choices that change as they learn from their productions. Their repertoires may also change, and the acquisition of behaviour is conditioned on its frequency. We analyse the diffusion of a novel behaviour through social networks, yielding generalizable predictions of how individual-level behavioural production rules influence population-level diffusion dynamics. We then investigate how linking acquisition and production might affect the performance of two commonly used inferential models for social learning; network-based diffusion analysis, and experience-weighted attraction models. We find that the influence that production rules have on diffusion dynamics has consequences for how inferential methods are applied to empirical data. Our model illuminates the differences between social learning and social influence, demonstrates the overlooked role of reinforcement learning in cultural diffusions, and allows for clearer discussions about social learning strategies.

Captive Asian short-clawed otters (Aonyx cinereus) learn to exploit unfamiliar natural prey.

Foraging plays a vital role in animal life histories, and learning whether unfamiliar food items are palatable is a key part of this process. Animals that engage in extractive foraging must also learn how to overcome the protective measures of their prey. While otters (subfamily Lutrinae) are a taxon known for their extractive foraging behaviour, how they learn about prey palatability and acquire extractive foraging techniques remains poorly understood. Here we investigated (i) how captive Asian short-clawed otters (Aonyx cinereus) learned to interact with, and extract meat from, unfamiliar natural prey and (ii) how their exploitation of such prey compared to their ability to overcome artificial foraging tasks containing familiar food rewards. Network-based diffusion analysis showed that otters learned to interact with unfamiliar natural prey by observing their group mates. However, once interacting with the prey, they learned to extract the meat mainly asocially. In addition, otters took longer to overcome the protective measures of unfamiliar natural prey than those of extractive food puzzles. Asian short-clawed otter populations are declining in the wild. Increasing our understanding of how they learn to overcome novel foraging challenges could help develop pre-release training procedures as part of reintroduction programmes for otter conservation.

Balance control in unstable sitting in individuals with an acute episode of low back pain.

BACKGROUND: Low back pain (LBP) is associated with altered postural control, mostly observed at later stages in the LBP trajectory. It is unclear whether postural control differs in the acute phase of LBP. RESEARCH QUESTION: Is postural control different in the acute phase of LBP (<2 weeks) and do differences depend on pain intensity, psychological features and/or availability of vision to control posture? METHODS: Cross-sectional study design. An unstable sitting paradigm (to reduce the contribution of the legs) assessed postural control of participants with acute LBP (n = 133) and pain-free controls (n = 74). Centre of pressure (CoP) reflected seat movements. Participants balanced with eyes closed, open, or with visual feedback of the anteroposterior CoP position. Balance performance was expressed by CoP displacement and velocity, and stabilogram diffusion analysis. Generalised estimating equations (GEEs) including body mass index, sex, and safety bar touch, tested differences between groups and between balance conditions. Separate GEEs were used to model performance measures and bar touch (yes/no) including pain intensity, disability and psychological features. RESULTS: CoP displacement and critical point coordinates (time and distance where CoP diffusion rate or spread slows) were larger in LBP than pain-free controls independent of balance condition. Long-term diffusion rate was greater in LBP than controls with eyes closed. CoP velocity measures (RMS, short term diffusion rate) were not different between groups. Pain intensity and psychological features were not linearly related to balance performance in participants with acute LBP. Higher pain catastrophizing was associated with touching the safety bar. SIGNIFICANCE: Postural control differs in acute LBP than pain-free controls. Findings might be explained by altered sensory processing, lesser ability to reweight proprioceptive information and/or less accurate trunk muscle control. Although not linearly related to pain-intensity or psychological features in the acute stage, reduced balance performance could potentially have impact on LBP recovery.

Trapping or slowing the diffusion of T cell receptors at close contacts initiates T cell signaling.

T cell activation is initiated by T cell receptor (TCR) phosphorylation. This requires the local depletion of large receptor-type phosphatases from "close contacts" formed when T cells interact with surfaces presenting agonistic TCR ligands, but exactly how the ligands potentiate signaling is unclear. It has been proposed that TCR ligands could enhance receptor phosphorylation and signaling just by holding TCRs in phosphatase-depleted close contacts, but this has not been directly tested. We devised simple methods to move the TCR in and out of close contacts formed by T cells interacting with supported lipid bilayers (SLBs) and to slow the receptor's diffusion in the contacts, using a series of anti-CD3ε Fab- and ligand-based adducts of the receptor. TCRs engaging a Fab extended with the large extracellular region of CD45 were excluded from contacts and produced no signaling. Conversely, allowing the extended Fab to become tethered to the SLB trapped the TCR in the close contacts, leading to very strong signaling. Importantly, attaching untethered anti-CD3ε Fab or peptide/MHC ligands, each of which were largely inactive in solution but both of which reduced TCR diffusion in close contacts approximately fivefold, also initiated signaling during cell/SLB contact. Our findings indicate that holding TCRs in close contacts or simply slowing their diffusion in phosphatase-depleted regions of the cell surface suffices to initiate signaling, effects we could reproduce in single-particle stochastic simulations. Our study shows that the TCR is preconfigured for signaling in a way that allows it to be triggered by ligands acting simply as receptor "traps."

Uncovering cellular networks in branching morphogenesis using single-cell transcriptomics.

Single-cell RNA-sequencing (scRNA-seq) and related technologies to identify cell types and measure gene expression in space, in time, and within lineages have multiplied rapidly in recent years. As these techniques proliferate, we are seeing an increase in their application to the study of developing tissues. Here, we focus on single-cell investigations of branching morphogenesis. Branched organs are highly complex but typically develop recursively, such that a given developmental stage theoretically contains the entire spectrum of cell identities from progenitor to terminally differentiated. Therefore, branched organs are a highly attractive system for study by scRNA-seq. First, we provide an update on advances in the field of scRNA-seq analysis, focusing on spatial transcriptomics, computational reconstruction of differentiation trajectories, and integration of scRNA-seq with lineage tracing. In addition, we discuss the possibilities and limitations for applying these techniques to studying branched organs. We then discuss exciting advances made using scRNA-seq in the study of branching morphogenesis and differentiation in mammalian organs, with emphasis on the lung, kidney, and mammary gland. We propose ways that scRNA-seq could be used to address outstanding questions in each organ. Finally, we highlight the importance of physical and mechanical signals in branching morphogenesis and speculate about how scRNA-seq and related techniques could be applied to study tissue morphogenesis beyond just differentiation.

Triexponential Diffusion Analysis of Diffusion-weighted Imaging for Breast Ductal Carcinoma in Situ and Invasive Ductal Carcinoma.

PURPOSE: To obtain detailed information in breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) using triexponential diffusion analysis. METHODS: Diffusion-weighted images (DWI) of the breast were obtained using single-shot diffusion echo-planar imaging with 15 b-values. Mean signal intensities at each b-value were measured in the DCIS and IDC lesions and fitted with the triexponential function based on a two-step approach: slow-restricted diffusion coefficient (Ds) was initially determined using a monoexponential function with b-values > 800 s/mm2. The diffusion coefficient of free water at 37°C was assigned to the fast-free diffusion coefficient (Df). Finally, the perfusion-related diffusion coefficient (Dp) was derived using all the b-values. Furthermore, biexponential analysis was performed to obtain the perfusion-related diffusion coefficient (D*) and the perfusion-independent diffusion coefficient (D). Monoexponential analysis was performed to obtain the apparent diffusion coefficient (ADC). The sensitivity and specificity of the aforementioned diffusion coefficients for distinguishing between DCIS and IDC were evaluated using the pathological results. RESULTS: The Ds, D, and ADC of DCIS were significantly higher than those of IDC (P < 0.01 for all). There was no significant correlation between Dp and Ds, but there was a weak correlation between D* and D. The combination of Dp and Ds showed higher sensitivity and specificity (85.9% and 71.4%, respectively), compared to the combination of D* and D (81.5% and 33.3%, respectively). CONCLUSION: Triexponential analysis can provide detailed diffusion information for breast tumors that can be used to differentiate between DCIS and IDC.

Diffusion analysis of fluid dynamics with incremental strength of motion proving gradient (DANDYISM) to evaluate cerebrospinal fluid dynamics.

PURPOSE: To visualize and analyze the dynamics of cerebrospinal fluid (CSF) motion in the cranium, we evaluated the distribution of motion-related signal dephasing by CSF on Diffusion ANalysis of fluid DYnamics with Incremental Strength of Motion proving gradient (DANDYISM) method, a composite imaging method using various low b values. MATERIALS AND METHODS: This study examined ten subjects aged 25-58. We acquired DWIs on a 3T clinical scanner with b values 0, 50, 100, 200, 300, 500, 700, and 1000 s/mm2 in total imaging time of 4 min. We constructed DANDYISM images and evaluated the CSF area distribution with decreased motion-dephasing signal using a scoring method. RESULTS: The DANDYISM images showed statistically significant higher CSF scores in the ventral posterior fossa, suprasellar cistern, and Sylvian vallecula compared to the lateral ventricle and frontal and parietal CSF spaces, indicating greater CSF movement in the former areas. CONCLUSION: The results indicated prominent CSF motions in the ventral portion of the posterior fossa, suprasellar cistern, and Sylvian fissure but smaller motions in the lateral ventricles and parietal subarachnoid space. This method may provide information of CSF dynamics in the clinical settings within short imaging time.

Detecting and quantifying social transmission using network-based diffusion analysis.

Although social learning capabilities are taxonomically widespread, demonstrating that freely interacting animals (whether wild or captive) rely on social learning has proved remarkably challenging. Network-based diffusion analysis (NBDA) offers a means for detecting social learning using observational data on freely interacting groups. Its core assumption is that if a target behaviour is socially transmitted, then its spread should follow the connections in a social network that reflects social learning opportunities. Here, we provide a comprehensive guide for using NBDA. We first introduce its underlying mathematical framework and present the types of questions that NBDA can address. We then guide researchers through the process of selecting an appropriate social network for their research question; determining which NBDA variant should be used; and incorporating other variables that may impact asocial and social learning. Finally, we discuss how to interpret an NBDA model's output and provide practical recommendations for model selection. Throughout, we highlight extensions to the basic NBDA framework, including incorporation of dynamic networks to capture changes in social relationships during a diffusion and using a multi-network NBDA to estimate information flow across multiple types of social relationship. Alongside this information, we provide worked examples and tutorials demonstrating how to perform analyses using the newly developed nbda package written in the R programming language.

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72 clinical strains of Klebsiella spp. isolated from samples obtained from humans in Novosibirsk, Russia, were analyzed. Species identification of strains was performed using 16S rRNA and rpoB gene sequences. It was revealed that Klebsiella pneumoniae strains were dominant in the population (57 strains), while the remaining 15 strains were K. grimontii, K. aerogenes, K. oxytoca and K. quasipneumoniae. By molecular serotyping using the wzi gene sequence, K. pneumoniae strains were assigned to twenty-one K-serotypes with a high proportion of virulent K1- and K2-serotypes. It was found that K. pneumoniae strains isolated from the hospitalized patients had a higher resistance to antibiotics compared to the other Klebsiella species. Real-time PCR revealed that the population contained genes of the blaSHV, blaTEM, blaCTX families and the blaOXA-48 gene, which are the genetic determinants of beta-lactam resistance. It has been shown that the presence of the blaCTX sequence correlated with the production of extended-spectrum beta-lactamases, and phenotypic resistance to carbapenems is due to the presence of the blaOXA-48 gene. At the same time, the carbapenemase genes vim, ndm, kpc, imp were not detected. Among the aminoglycoside resistance genes studied, the aph(6)-Id and aadA genes were found, but their presence did not always coincide with phenotypic resistance. Resistance to fluoroquinolones in the vast majority of strains was accompanied by the presence of the aac(6')-IB-cr, oqxA, oqxB, qnrB, and qnrS genes in various combinations, while the presence of the oqxA and/or oqxB genes alone did not correlate with resistance to fluoroquinolones. Thus, the detection of blaCTX and blaOXA-48 can be used to quickly predict the production of extended-spectrum beta-lactamases and to determine the resistance of Klebsiella to carbapenems. The detection of the aac(6')-Ib-cr and/or qnrB/qnrS genes can be used to quickly determine resistance to fluoroquinolones.

Personality composition determines social learning pathways within shoaling fish.

In shaping how individuals explore their environment and interact with others, personality may mediate both individual and social learning. Yet increasing evidence indicates that personality expression is contingent on social context, suggesting that group personality composition may be key in determining how individuals learn about their environment. Here, we used recovery latency following simulated predator attacks to identify Trinidadian guppies (Poecilia reticulata) that acted in a consistently bold or shy manner. We then employed network-based diffusion analysis to track the spread of a novel foraging behaviour through groups containing different proportions of bold and shy fish. Informed associates promoted learning to a greater extent in bold individuals, but only within groups composed predominately of bold fish. As the proportion of shy fish within groups increased, bold individuals instead emerged as especially effective demonstrators that facilitated learning in others. Individuals were also more likely to learn overall within shy-dominated groups than in bold-dominated ones. We demonstrate that whether and how individuals learn is conditional on group personality composition, indicating that selection may favour traits enabling individuals to better match their behavioural phenotype to their social environment.

Integrating Genetic, Environmental, and Social Networks to Reveal Transmission Pathways of a Dolphin Foraging Innovation.

Cultural behavior, which is transmitted among conspecifics through social learning [1], is found across various taxa [2-6]. Vertical social transmission from parent to offspring [7] is thought to be adaptive because of the parental generation being more skilled than maturing individuals. It is found throughout the animal kingdom, particularly in species with prolonged parental care, e.g., [8, 9]. Social learning can also occur among members of the same generation [4, 10, 11] or between older, non-parental individuals and younger generations [7] via horizontal or oblique transmission, respectively. Extensive work on primate culture has shown that horizontal transmission of foraging behavior is biased toward species with broad cultural repertoires [12] and those with increased levels of social tolerance [13, 14], such as great apes. Vertical social transmission has been established as the primary transmission mechanism of foraging behaviors in the Indo-Pacific bottlenose dolphin (Tursiops aduncus) population of Shark Bay, Western Australia [6, 9, 15, 16]. Here, we investigated the spread of another foraging strategy, "shelling" [17], whereby some dolphins in this population feed on prey trapped inside large marine gastropod shells. Using a multi-network version of "network-based diffusion analysis" (NBDA), we show that shelling behavior spreads primarily through non-vertical social transmission. By statistically accounting for both environmental and genetic influences, our findings thus represent the first evidence of non-vertical transmission of a foraging tactic in toothed whales. This research suggests there are multiple transmission pathways of foraging behaviors in dolphins, highlighting the similarities between cetaceans and great apes in the nature of the transmission of cultural behaviors. VIDEO ABSTRACT.

Influence of Dominance and Drift on Lethal Mutations in Human Populations.

We consider disease-causing mutations that are lethal when homozygous. Lethality involves the very strongest form of negative selection, with the selection coefficient against the disease-carrying homozygote having its maximum value of unity. We determine results for the behavior of the frequency of a lethal allele in an effectively infinite population. This includes an estimate of the time it takes to achieve equilibrium, and a description of transient behavior associated with a sudden change in the fitness of the heterozygote. We determine analogous results for a finite population, showing that a lethal disease-causing allele needs to be described by a modified Wright-Fisher model, which deviates from the standard model, where selection coefficients are assumed small compared with 1. We show that a by-product of the dynamics, resulting from the absence of the disease-allele carrying homozygote in adults, is the general constraint that the frequency of the disease-causing allele cannot exceed 1 2 . The results presented in this work should prove useful to a number of areas including analysis of lethal/near lethal mutations in Mendelian disorders and, in particular, for exploring how mutation-selection-drift balance explains the current spectrum of mutation frequencies in humans. While the number of empirical examples of overdominance in lethal genetic disorders is not large, relatively high observed heterozygote frequencies may be a hint of transient heterozygous advantage in nature. For lethal disorders with anomalous frequencies, such as cystic fibrosis and Tay-Sachs, our analysis lends further support to the role that transitory episodes of weak overdominance may play in the evolution of lethal mutations.

Fatigue-related modulation of low-frequency common drive to motor units.

PURPOSE: This study investigated fatigue-related modulation of common neural inputs to motor units (MUs) under 5 Hz, which determines force precision control. METHODS: Twenty-seven adults performed a sequence of fatiguing contractions. The participants were assessed with a static isometric index abduction at 20% maximal voluntary contraction in the pre-test and post-test. Discharge characteristics of MUs of the first dorsal interosseous muscle were analyzed with decomposed EMG signals. RESULTS: Along with increases in the mean (58.40 ± 11.76 ms → 62.55 ± 10.83 ms, P = 0.029) and coefficient of variation (0.204 ± .014 → 0.215 ± 0.017, P = 0.002) in inter-spike intervals, the fatiguing contraction caused reductions in the mean frequency (16.84 ± 3.31 Hz → 15.59 ± 3.21 Hz, P = 0.027) and spectral dispersions (67.54 ± 4.49 → 62.64 ± 6.76 Hz, P = 0.007) of common neural drive, as estimated with smoothed cumulative motor unit spike trains (SCMUSTs). Stabilogram diffusion analysis of SCMUSTs revealed significant fatigue-related reductions in the long-term effective diffusion coefficient (1.91 ± 0.77 Hz2/s → 1.61 ± 0.61 Hz2/s, P = 0.020) and long-term scaling exponent (0.480 ± 0.013 Hz2/s → 0.471 ± 0.017 Hz2/s, P = 0.014). After fatiguing contraction, mutual information of force fluctuations and SCMUSTs was augmented roughly by 12.95% (P = 0.041). CONCLUSIONS: Muscular fatigue could compress and shift the low-frequency common drive to MUs toward lower spectral bands, thereby enhancing transmission of twitch forces through the muscle-tendon complex with a low-pass filter property. The fatigue-induced changes involve increased closed-loop control of the common modulation of MU discharge rates.