A Minimal Model of Metabolism Based Chemotaxis

Since the pioneering work by Julius Adler in the 1960's, bacterial chemotaxis has been predominantly studied as metabolism-independent. All available simulation models of bacterial chemotaxis endorse this assumption. Recent studies have shown, however, that many metabolism-dependent chemotactic patterns occur in bacteria. We hereby present the simplest artificial protocell model capable of performing metabolism-based chemotaxis. The model serves as a proof of concept to show how even the simplest metabolism can sustain chemotactic patterns of varying sophistication. It also reproduces a set of phenomena that have recently attracted attention on bacterial chemotaxis and provides insights about alternative mechanisms that could instantiate them. We conclude that relaxing the metabolism-independent assumption provides important theoretical advances, forces us to rethink some established pre-conceptions and may help us better understand unexplored and poorly understood aspects of bacterial chemotaxis

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Molecular phylogeny and timing of diversification in Alpine Rhithrogena (Ephemeroptera: Heptageniidae).

BACKGROUND: Larvae of the Holarctic mayfly genus Rhithrogena Eaton, 1881 (Ephemeroptera, Heptageniidae) are a diverse and abundant member of stream and river communities and are routinely used as bio-indicators of water quality. Rhithrogena is well diversified in the European Alps, with a number of locally endemic species, and several cryptic species have been recently detected. While several informal species groups are morphologically well defined, a lack of reliable characters for species identification considerably hampers their study. Their relationships, origin, timing of speciation and mechanisms promoting their diversification in the Alps are unknown. RESULTS: Here we present a species-level phylogeny of Rhithrogena in Europe using two mitochondrial and three nuclear gene regions. To improve sampling in a genus with many cryptic species, individuals were selected for analysis according to a recent DNA-based taxonomy rather than traditional nomenclature. A coalescent-based species tree and a reconstruction based on a supermatrix approach supported five of the species groups as monophyletic. A molecular clock, mapped on the most resolved phylogeny and calibrated using published mitochondrial evolution rates for insects, suggested an origin of Alpine Rhithrogena in the Oligocene/Miocene boundary. A diversification analysis that included simulation of missing species indicated a constant speciation rate over time, rather than any pronounced periods of rapid speciation. Ancestral state reconstructions provided evidence for downstream diversification in at least two species groups. CONCLUSIONS: Our species-level analyses of five gene regions provide clearer definitions of species groups within European Rhithrogena. A constant speciation rate over time suggests that the paleoclimatic fluctuations, including the Pleistocene glaciations, did not significantly influence the tempo of diversification of Alpine species. A downstream diversification trend in the hybrida and alpestris species groups supports a previously proposed headwater origin hypothesis for aquatic insects

Lutetium-labelled peptides for therapy of neuroendocrine tumours

Treatment with radiolabelled somatostatin analogues is a promising new tool in the management of patients with inoperable or metastasized neuroendocrine tumours. Symptomatic improvement may occur with 177Lu-labelled somatostatin analogues that have been used for peptide receptor radionuclide therapy (PRRT). The results obtained with 177Lu-[DOTA0,Tyr3]octreotate (DOTATATE) are very encouraging in terms of tumour regression. Dosimetry studies with 177Lu-DOTATATE as well as the limited side effects with additional cycles of 177Lu-DOTATATE suggest that more cycles of 177Lu-DOTATATE can be safely given. Also, if kidney-protective agents are used, the side effects of this therapy are few and mild and less than those from the use of 90Y-[DOTA0,Tyr3]octreotide (DOTATOC). Besides objective tumour responses, the median progression-free survival is more than 40 months. The patients' self-assessed quality of life increases significantly after treatment with 177Lu-DOTATATE. Lastly, compared to historical controls, there is a benefit in overall survival of several years from the time of diagnosis in patients treated with 177Lu-DOTATATE. These findings compare favourably with the limited number of alternative therapeutic approaches. If more widespread use of PRRT can be guaranteed, such therapy may well become the therapy of first choice in patients with metastasized or inoperable neuroendocrine tumours

Mechanical Strain Regulates Osteoblast Proliferation through Integrin-Mediated ERK Activation

Mechanical strain plays a critical role in the proliferation, differentiation and maturation of bone cells. As mechanical receptor cells, osteoblasts perceive and respond to stress force, such as those associated with compression, strain and shear stress. However, the underlying molecular mechanisms of this process remain unclear. Using a four-point bending device, mouse MC3T3-E1 cells was exposed to mechanical tensile strain. Cell proliferation was determined to be most efficient when stimulated once a day by mechanical strain at a frequency of 0.5 Hz and intensities of 2500 µε with once a day, and a periodicity of 1 h/day for 3 days. The applied mechanical strain resulted in the altered expression of 1992 genes, 41 of which are involved in the mitogen-activated protein kinase (MAPK) signaling pathway. Activation of ERK by mechanical strain promoted cell proliferation and inactivation of ERK by PD98059 suppressed proliferation, confirming that ERK plays an important role in the response to mechanical strain. Furthermore, the membrane-associated receptors integrin β1 and integrin β5 were determined to regulate ERK activity and the proliferation of mechanical strain-treated MC3T3-E1 cells in opposite ways. The knockdown of integrin β1 led to the inhibition of ERK activity and cell proliferation, whereas the knockdown of integrin β5 led to the enhancement of both processes. This study proposes a novel mechanism by which mechanical strain regulates bone growth and remodeling

Empowering Qualitative Research Methods in Education with Artificial Intelligence

Artificial Intelligence is one of the fastest growing disciplines, disrupting many sectors. Originally mainly for computer scientists and engineers, it has been expanding its horizons and empowering many other disciplines contributing to the development of many novel applications in many sectors. These include medicine and health care, business and finance, psychology and neuroscience, physics and biology to mention a few. However, one of the disciplines in which artificial intelligence has not been fully explored and exploited yet is education. In this discipline, many research methods are employed by scholars, lecturers and practitioners to investigate the impact of different instructional approaches on learning and to understand the ways skills and knowledge are acquired by learners. One of these is qualitative research, a scientific method grounded in observations that manipulates and analyses non-numerical data. It focuses on seeking answers to why and how a particular observed phenomenon occurs rather than on its occurrences. This study aims to explore and discuss the impact of artificial intelligence on qualitative research methods. In particular, it focuses on how artificial intelligence have empowered qualitative research methods so far, and how it can be used in education for enhancing teaching and learning