Verreaux’s Eagle Owl Bubo lacteus attacked by Thick-billed Ravens Corvus crassirostris

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Structural phase transition in IrTe2_2: A combined study of optical spectroscopy and band structure calculations

Ir$_{1-x}$Pt$_x$Te$_2$ is an interesting system showing competing phenomenon between structural instability and superconductivity. Due to the large atomic numbers of Ir and Te, the spin-orbital coupling is expected to be strong in the system which may lead to nonconventional superconductivity. We grew single crystal samples of this system and investigated their electronic properties. In particular, we performed optical spectroscopic measurements, in combination with density function calculations, on the undoped compound IrTe$_2$ in an effort to elucidate the origin of the structural phase transition at 280 K. The measurement revealed a dramatic reconstruction of band structure and a significant reduction of conducting carriers below the phase transition. We elaborate that the transition is not driven by the density wave type instability but caused by the crystal field effect which further splits/separates the energy levels of Te (p$_x$, p$_y$) and Te p$_z$ bands.Comment: 16 pages, 5 figure

Diurnal variability of inner-shelf circulation in the lee of a cape under upwelling conditions.

The nearshore circulation in the lee of a cape under upwelling conditions was studied using in-situ data from 3 consecutive summers (2006–2008). Focus was given to a period between 20 July and 04 August 2006 to study the diurnal variability of the cross-shelf circulation. This period was chosen because it had a steady upwellingfavourable wind condition modulated by a diurnal cycle much similar to sea breeze. The daily variability of the observed cross-shelf circulation consisted of three distinct periods: a morning period with a 3-layer vertical structure with onshore velocities at mid-depth, a mid-day period where the flow is reversed and has a 2-layer structure with onshore velocities at the surface and offshore flow below, and, lastly, in the evening, a 2-layer period with intensified offshore velocities at the surface and onshore flow at the bottom. The observed cross-shelf circulation showed a peculiar vertical shape and diurnal variability different from several other systems described in literature. We hypothesize that the flow reversal of the cross-shelf circulation results as a response to the rapid change of the wind magnitude and direction at mid-day with the presence of the cape north of the mooring site influencing this response. A numerical modelling experiment exclusively forced by winds simulated successfully most of the circulation at the ADCP site, especially the mid-day reversal and the evening's upwelling-type structure. This supports the hypothesis that the cross-shelf circulation at diurnal timescales is mostly wind-driven. By analysing the 3D circulation in the vicinity of Cape Sines we came to the conclusion that the diurnal variability of the wind and the flow interaction with topography are responsible for the circulation variability at the ADCP site, though only a small region in the south of the cape showed a similar diurnal variability. The fact that the wind diurnally undergoes relaxation and intensification strongly affects the circulation, promoting superficial onshore flows in the leeside of Cape Sines. Despite the small-scale nature of the observed cross-shelf circulation, onshore flows as the ones described in this study can be particularly helpful to understand the transport and settlement of larvae in this region and in other regions with similar topography and wind characteristics.We thank D. Jacinto and T. Silva for help during field work and the Port of Sines Authority (APS) for providing oceanographic and meteorological data. Financial support was provided by FCT (POCI/ MAR/57630/2004; PTDC/BIA-BEC/103734/2008 and PEst-OE/ MAR/UIO199/2011). The simulations were preformed in the computational facilities provided under FCT contract RECI/GEO-MET/0380/ 2012. Luísa Lamas was funded by the FCT under a Ph.D. grant (SFRH/ BD/69533/2010)

Prevention of cardiovascular disease in patients with familial hypercholesterolaemia: the role of PCSK9 inhibitors

Familial hypercholesterolaemia is an autosomal dominant inherited disorder characterised by elevated low-density lipoprotein cholesterol levels and consequently an increased risk of atherosclerotic cardiovascular disease (ASCVD). Familial hypercholesterolaemia is relatively common, but is often underdiagnosed and undertreated. Cardiologists are likely to encounter many individuals with familial hypercholesterolaemia; however, patients presenting with premature ASCVD are rarely screened for familial hypercholesterolaemia and fasting lipid levels are infrequently documented. Given that individuals with familial hypercholesterolaemia and ASCVD are at a particularly high risk of subsequent cardiac events, this is a missed opportunity for preventive therapy. Furthermore, because there is a 50% chance that first-degree relatives of individuals with familial hypercholesterolaemia will also be affected by the disorder, the underdiagnosis of familial hypercholesterolaemia among patients with ASCVD is a barrier to cascade screening and the prevention of ASCVD in affected relatives. Targeted screening of patients with ASCVD is an effective strategy to identify new familial hypercholesterolaemia index cases. Statins are the standard treatment for individuals with familial hypercholesterolaemia; however, low-density lipoprotein cholesterol targets are not achieved in a large proportion of patients despite treatment. Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors have been shown to reduce low-density lipoprotein cholesterol levels considerably in individuals with familial hypercholesterolaemia who are concurrently receiving the maximal tolerated statin dose. The clinical benefit of PCSK9 inhibitors must, however, also be considered in terms of their cost-effectiveness. Increased awareness of familial hypercholesterolaemia is required among healthcare professionals, particularly cardiologists and primary care physicians, in order to start early preventive measures and to reduce the mortality and morbidity associated with familial hypercholesterolaemia and ASCVD

Machine learning predicts 3D printing performance of over 900 drug delivery systems

Three-dimensional printing (3DP) is a transformative technology that is advancing pharmaceutical research by producing personalized drug products. However, advances made via 3DP have been slow due to the lengthy trial-and-error approach in optimization. Artificial intelligence (AI) is a technology that could revolutionize pharmaceutical 3DP through analyzing large datasets. Herein, literature-mined data for developing AI machine learning (ML) models was used to predict key aspects of the 3DP formulation pipeline and in vitro dissolution properties. A total of 968 formulations were mined and assessed from 114 articles. The ML techniques explored were able to learn and provide accuracies as high as 93% for values in the filament hot melt extrusion process. In addition, ML algorithms were able to use data from the composition of the formulations with additional input features to predict the drug release of 3D printed medicines. The best prediction was obtained by an artificial neural network that was able to predict drug release times of a formulation with a mean error of ±24.29 min. In addition, the most important variables were revealed, which could be leveraged in formulation development. Thus, it was concluded that ML proved to be a suitable approach to modelling the 3D printing workflow

Predicting pharmaceutical inkjet printing outcomes using machine learning

Inkjet printing has been extensively explored in recent years to produce personalised medicines due to its low cost and versatility. Pharmaceutical applications have ranged from orodispersible films to complex polydrug implants. However, the multi-factorial nature of the inkjet printing process makes formulation (e.g., composition, surface tension, and viscosity) and printing parameter optimization (e.g., nozzle diameter, peak voltage, and drop spacing) an empirical and time-consuming endeavour. Instead, given the wealth of publicly available data on pharmaceutical inkjet printing, there is potential for a predictive model for inkjet printing outcomes to be developed. In this study, machine learning (ML) models (random forest, multilayer perceptron, and support vector machine) to predict printability and drug dose were developed using a dataset of 687 formulations, consolidated from in-house and literature-mined data on inkjet-printed formulations. The optimized ML models predicted the printability of formulations with an accuracy of 97.22%, and predicted the quality of the prints with an accuracy of 97.14%. This study demonstrates that ML models can feasibly provide predictive insights to inkjet printing outcomes prior to formulation preparation, affording resource- and time-savings

PROP1 gene analysis in Portuguese patients with combined pituitary hormone deficiency

OBJECTIVE: Mutations of the PROP1 gene lead to combined pituitary hormone deficiency (CPHD), which is characterized by a deficiency of GH, TSH, LH/FSH, PRL and, less frequently, ACTH. This study was undertaken to investigate the molecular defect in a cohort of patients with CPHD. DESIGN, PATIENTS AND MEASUREMENTS: A multicentric study involving 46 cases of CPHD (17 familial cases belonging to seven kindreds and 29 sporadic cases) selected on the basis of clinical and hormonal evidence of GH deficiency, central hypothyroidism and hypogonadotrophic hypogonadism, in the absence of an identified cause of hypopituitarism. Mutations of PROP1 were investigated by DNA sequencing. Clinical, hormonal and neuroradiological data were collected at each centre. RESULTS: PROP1 mutations were identified in all familial cases: five kindreds presented a c. 301-302delAG mutation, one kindred presented a c. 358C --> T (R120C) mutation and one presented a previously unreported initiation codon mutation, c. 2T --> C. Of the 29 sporadic cases, only two (6.9%) presented PROP1 germline mutations (c. 301-302delAG, in both). Phenotypic variability was observed among patients with the same mutations, particularly the presence and age of onset of hypocortisolism, the levels of PRL and the results of pituitary imaging. One patient presented a sellar mass that persisted into adulthood. CONCLUSIONS: This is the first report of a mutation in the initiation codon of the PROP1 gene and this further expands the spectrum of known mutations responsible for CPHD. The low mutation frequency observed in sporadic cases may be due to the involvement of other unidentified acquired or genetic cause

Patterns of subnet usage reveal distinct scales of regulation in the transcriptional regulatory network of Escherichia coli

The set of regulatory interactions between genes, mediated by transcription factors, forms a species' transcriptional regulatory network (TRN). By comparing this network with measured gene expression data one can identify functional properties of the TRN and gain general insight into transcriptional control. We define the subnet of a node as the subgraph consisting of all nodes topologically downstream of the node, including itself. Using a large set of microarray expression data of the bacterium Escherichia coli, we find that the gene expression in different subnets exhibits a structured pattern in response to environmental changes and genotypic mutation. Subnets with less changes in their expression pattern have a higher fraction of feed-forward loop motifs and a lower fraction of small RNA targets within them. Our study implies that the TRN consists of several scales of regulatory organization: 1) subnets with more varying gene expression controlled by both transcription factors and post-transcriptional RNA regulation, and 2) subnets with less varying gene expression having more feed-forward loops and less post-transcriptional RNA regulation.Comment: 14 pages, 8 figures, to be published in PLoS Computational Biolog

Simultaneous fabrication of multiple tablets within seconds using tomographic volumetric 3D printing

3D printing is driving a shift in patient care away from a generalised model and towards personalised treatments. To complement fast-paced clinical environments, 3D printing technologies must provide sufficiently high throughputs for them to be feasibly implemented. Volumetric printing is an emerging 3D printing technology that affords such speeds, being capable of producing entire objects within seconds. In this study, for the first time, rotatory volumetric printing was used to simultaneously produce two torus- or cylinder-shaped paracetamol-loaded Printlets (3D printed tablets). Six resin formulations comprising paracetamol as the model drug, poly(ethylene glycol) diacrylate (PEGDA) 575 or 700 as photoreactive monomers, water and PEG 300 as non-reactive diluents, and lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP) as the photoinitiator were investigated. Two printlets were successfully printed in 12 to 32 s and exhibited sustained drug release profiles. These results support the use of rotary volumetric printing for efficient and effective manufacturing of various personalised medicines at the same time. With the speed and precision it affords, rotatory volumetric printing has the potential to become one of the most promising alternative manufacturing technologies in the pharmaceutical industry

Control over phase separation and nucleation using a laser-tweezing potential

Control over the nucleation of new phases is highly desirable but elusive. Even though there is a long history of crystallization engineering by varying physicochemical parameters, controlling which polymorph crystallizes or whether a molecule crystallizes or forms an amorphous precipitate is still a poorly understood practice. Although there are now numerous examples of control using laser-induced nucleation, the absence of physical understanding is preventing progress. Here we show that the proximity of a liquid–liquid critical point or the corresponding binodal line can be used by a laser-tweezing potential to induce concentration gradients. A simple theoretical model shows that the stored electromagnetic energy of the laser beam produces a free-energy potential that forces phase separation or triggers the nucleation of a new phase. Experiments in a liquid mixture using a low-power laser diode confirm the effect. Phase separation and nucleation using a laser-tweezing potential explains the physics behind non-photochemical laser-induced nucleation and suggests new ways of manipulating matter