The effect of increasing heel height on lower limb symmetry during the back squat in trained and novice lifters

Background: Symmetry during lifting is considered critical for allowing balanced power production and avoidance of injury. This investigation assessed the influence of elevating the heels on bilateral lower limb symmetry during loaded (50% of body weight) high-bar back squats. Methods: Ten novice (mass 67.6 ± 12.4 kg, height 1.73 ± 0.10 m) and ten regular weight trainers (mass 66.0 ± 10.7 kg, height 1.71 ± 0.09 m) were assessed while standing on both the flat level floor and on an inclined board. Data collection used infra-red motion capture procedures and two force platforms to record bilateral vertical ground reaction force (GRFvert) and ankle, knee and hip joint kinematic and kinetic data. Paired t-tests and statistical parametric mapping (SPM1D) procedures were used to assess differences in discrete and continuous bilateral symmetry data across conditions. Results: Although discrete joint kinematic and joint moment symmetry data were largely unaffected by raising the heels, the regular weight trainers presented greater bilateral asymmetry in these data than the novices. The one significant finding in these discrete data showed that raising the heels significantly reduced maximum knee extension moment asymmetry (P = 0.02), but in the novice group only. Time-series analyses indicated significant bilateral asymmetries in both GRFvert and knee extension moments mid-way though the eccentric phase for the novice group, with the latter unaffected by heel lift condition. There were no significant bilateral asymmetries in time series data within the regular weight training group. Conclusions: This investigation highlights that although a degree of bilateral lower limb asymmetry is common in individuals performing back squats, the degree of this symmetry is largely unaffected by raising the heels. Differences in results for discrete and time-series symmetry analyses also highlight a key issue associated with relying solely on discrete data techniques to assess bilateral symmetry during tasks such as the back squat

Sequencing the potato genome: outline and first results to come from the elucidation of the sequence of the world's third most important food crop

Potato is a member of the Solanaceae, a plant family that includes several other economically important species, such as tomato, eggplant, petunia, tobacco and pepper. The Potato Genome Sequencing Consortium (PGSC) aims to elucidate the complete genome sequence of potato, the third most important food crop in the world. The PGSC is a collaboration between 13 research groups from China, India, Poland, Russia, the Netherlands, Ireland, Argentina, Brazil, Chile, Peru, USA, New Zealand and the UK. The potato genome consists of 12 chromosomes and has a (haploid) length of approximately 840 million base pairs, making it a medium-sized plant genome. The sequencing project builds on a diploid potato genomic bacterial artificial chromosome (BAC) clone library of 78000 clones, which has been fingerprinted and aligned into ~7000 physical map contigs. In addition, the BAC-ends have been sequenced and are publicly available. Approximately 30000 BACs are anchored to the Ultra High Density genetic map of potato, composed of 10000 unique AFLPTM markers. From this integrated genetic-physical map, between 50 to 150 seed BACs have currently been identified for every chromosome. Fluorescent in situ hybridization experiments on selected BAC clones confirm these anchor points. The seed clones provide the starting point for a BAC-by-BAC sequencing strategy. This strategy is being complemented by whole genome shotgun sequencing approaches using both 454 GS FLX and Illumina GA2 instruments. Assembly and annotation of the sequence data will be performed using publicly available and tailor-made tools. The availability of the annotated data will help to characterize germplasm collections based on allelic variance and to assist potato breeders to more fully exploit the genetic potential of potat

The Ukraine-Russia war : a symptoms network of complex posttraumatic stress disorder during continuous traumatic stress

Objective: This study is aimed to test the symptoms network of ICD-11 Complex Post-traumatic Stress Disorder (CPTSD) symptoms, using data collected from Ukrainian civilians during the 2022 Russia-Ukraine war. Findings can inform our understanding of the stress response in individuals exposed to continuous trauma and give insight into the nature of CPTSD during war. Methods: A network analysis was conducted on CPTSD symptoms as assessed by the International Trauma Questionnaire using data from a nationally representative sample of 2000 Ukrainians. Results: While Post-traumatic Stress Disorder (PTSD) and Disturbances in Self Organization (DSO) clusters did not enmesh, several communities within these clusters were merged. Results highlight that in terms of strength centrality, emotional dysregulation (emotional numbing) and a heightened sense of threat were most prominent. Conclusion: The results confirm the ICD-11 structure of CPTSD but suggest that continuous traumatic stress manifests in more condensed associations between CPTSD symptoms and that emotional regulation may play a vital role in activating the CPTSD network. War-exposed populations could be provided with scalable, brief self-help materials focused on fostering emotion regulation and sense of threat

Synchronization of developmental, molecular and metabolic aspects of source–sink interactions

Plants have evolved a multitude of strategies to adjust their growth according to external and internal signals. Interconnected metabolic and phytohormonal signalling networks allow adaption to changing environmental and developmental conditions and ensure the survival of species in fluctuating environments. In agricultural ecosystems, many of these adaptive responses are not required or may even limit crop yield, as they prevent plants from realizing their fullest potential. By lifting source and sink activities to their maximum, massive yield increases can be foreseen, potentially closing the future yield gap resulting from an increasing world population and the transition to a carbon-neutral economy. To do so, a better understanding of the interplay between metabolic and developmental processes is required. In the past, these processes have been tackled independently from each other, but coordinated efforts are required to understand the fine mechanics of source–sink relations and thus optimize crop yield. Here, we describe approaches to design high-yielding crop plants utilizing strategies derived from current metabolic concepts and our understanding of the molecular processes determining sink development.Research in the authors’ laboratories was supported by the following grants: the cassava source–sink (CASS) project of the Bill and Melinda Gates Foundation (to A.R.F., H.E.N., M.S. and U.S.); the ERA-CAPs project SourSi (to A.R.F. and L.J.S.); the BIO2015-3019-EXP grant from the Spanish Ministry of Economy, Industry and Competitiveness and the PCIN-2017-032 CONCERT-JAPAN project financed by the Ministry of Science, Innovation and Universities (to S.P.); Australian Research Council DP180103834 (to Y.L.R.); the US National Science Foundation (grant no. IOS-1457183); the Agriculture and Food Research Initiative (AFRI; grant no. 2017-67013-26158) from the USDA National Institute of Food and Agriculture (to M.T.); the Finnish Centre of Excellence in Molecular Biology of Primary Producers (Academy of Finland CoE program 2014–2019; grant no. 271832); the Gatsby Foundation (grant no. GAT3395/PR3); the University of Helsinki (grant no. 799992091); the European Research Council Advanced Investigator Grant SYMDEV (grant no. 323052; to Y.H.); the BMBF (grant no. 031B0191); the DFG (SPP1530: WA3639/1-2, 2-1); and the Max-Planck-Society (to V.W.). We additionally thank D. Ko and R. Ruonala for their comments on the manuscript

Deterministic approach to microscopic three-phase traffic theory

Two different deterministic microscopic traffic flow models, which are in the context of the Kerner's there-phase traffic theory, are introduced. In an acceleration time delay model (ATD-model), different time delays in driver acceleration associated with driver behaviour in various local driving situations are explicitly incorporated into the model. Vehicle acceleration depends on local traffic situation, i.e., whether a driver is within the free flow, or synchronized flow, or else wide moving jam traffic phase. In a speed adaptation model (SA-model), vehicle speed adaptation occurs in synchronized flow depending on driving conditions. It is found that the ATD- and SA-models show spatiotemporal congested traffic patterns that are adequate with empirical results. In the ATD- and SA-models, the onset of congestion in free flow at a freeway bottleneck is associated with a first-order phase transition from free flow to synchronized flow; moving jams emerge spontaneously in synchronized flow only. Differences between the ATD- and SA-models are studied. A comparison of the ATD- and SA-models with stochastic models in the context of three phase traffic theory is made. A critical discussion of earlier traffic flow theories and models based on the fundamental diagram approach is presented.Comment: 40 pages, 14 figure

Efficient Symbolic Representation of Convex Polyhedra in High-Dimensional Spaces

peer reviewedThis work is aimed at developing an efficient data structure for representing symbolically convex polyhedra. We introduce an original data structure, the Decomposed Convex Polyhedron (DCP), that is closed under intersection and linear transformations, and allows to check inclusion, equality, and emptiness. The main feature of DCPs lies in their ability to represent concisely polyhedra that can be expressed as combinations of simpler sets, which can overcome combinatorial explosion in high dimensional spaces. DCPs also have the advantage of being reducible into a canonical form, which makes them efficient for representing simple sets constructed by long sequences of manipulations, such as those handled by state-space exploration tools. Their practical efficiency has been evaluated with the help of a prototype implementation, with promising results

A remote secondary binding pocket promotes heteromultivalent targeting of DC-SIGN

Dendritic cells (DC) are antigen-presenting cells coordinating the interplay of the innate and the adaptive immune response. The endocytic C-type lectin receptors DC-SIGN and Langerin display expression profiles restricted to distinct DC subtypes and have emerged as prime targets for next-generation immunotherapies and anti-infectives. Using heteromultivalent liposomes copresenting mannosides bearing aromatic aglycones with natural glycan ligands, we serendipitously discovered striking cooperativity effects for DC-SIGN+ but not for Langerin+ cell lines. Mechanistic investigations combining NMR spectroscopy with molecular docking and molecular dynamics simulations led to the identification of a secondary binding pocket for the glycomimetics. This pocket, located remotely of DC-SIGN’s carbohydrate bindings site, can be leveraged by heteromultivalent avidity enhancement. We further present preliminary evidence that the aglycone allosterically activates glycan recognition and thereby contributes to DC-SIGN-specific cell targeting. Our findings have important implications for both translational and basic glycoscience, showcasing heteromultivalent targeting of DCs to improve specificity and supporting potential allosteric regulation of DC-SIGN and CLRs in general

Chronic hyperglycemia induces trans-differentiation of human pancreatic stellate cells and enhances the malignant molecular communication with human pancreatic cancer cells

BACKGROUND: Diabetes mellitus is linked to pancreatic cancer. We hypothesized a role for pancreatic stellate cells (PSC) in the hyperglycemia induced deterioration of pancreatic cancer and therefore studied two human cell lines (RLT-PSC, T3M4) in hyperglycemic environment. METHODOLOGY/PRINCIPAL FINDINGS: The effect of chronic hyperglycemia (CHG) on PSCs was studied using mRNA expression array with real-time PCR validation and bioinformatic pathway analysis, and confirmatory protein studies. The stress fiber formation (IC: αSMA) indicated that PSCs tend to transdifferentiate to a myofibroblast-like state after exposure to CHG. The phosphorylation of p38 and ERK1/2 was increased with a consecutive upregulation of CDC25, SP1, cFOS and p21, and with downregulation of PPARγ after PSCs were exposed to chronic hyperglycemia. CXCL12 levels increased significantly in PSC supernatant after CHG exposure independently from TGF-β1 treatment (3.09-fold with a 2.73-fold without TGF-β1, p<0.05). The upregualtion of the SP1 transcription factor in PSCs after CHG exposure may be implicated in the increased CXCL12 and IGFBP2 production. In cancer cells, hyperglycemia induced an increased expression of CXCR4, a CXCL12 receptor that was also induced by PSC's conditioned medium. The receptor-ligand interaction increased the phosphorylation of ERK1/2 and p38 resulting in activation of MAP kinase pathway, one of the most powerful stimuli for cell proliferation. Certainly, conditioned medium of PSC increased pancreatic cancer cell proliferation and this effect could be partially inhibited by a CXCR4 inhibitor. As the PSC conditioned medium (normal glucose concentration) increased the ERK1/2 and p38 phosphorylation, we concluded that PSCs produce other factor(s) that influence(s) pancreatic cancer behaviour. CONCLUSIONS: Hyperglycemia induces increased CXCL12 production by the PSCs, and its receptor, CXCR4 on cancer cells. The ligand-receptor interaction activates MAP kinase signaling that causes increased cancer cell proliferation and migration