Assessment of wood load condition by Near Infrared (NIR) spectroscopy

The assessment of the mechanical properties of wood using non-destructive evaluation (NDE) tools has been widely developed and refined. These NDE tools mainly rely on vibrational, ultrasonic or stress-wave approaches. Vibrational techniques generally show higher correlations between the estimated modulus of elasticity (MOE), or modulus of rupture (MOR), and the measured MOE, or MOR, than stress-wave techniques. They are, however, relatively difficult to apply in the field due to boundary conditions common in many timber structures. Thus, improved tools for assessing timber structures are still needed. Recently, near infrared (NIR) spectroscopy (500–2400 nm) has shown promise for predicting the MOE and MOR of wood. This work focuses on extending the use of NIR for measuring the load applied to small wood beams. The reflectance NIR spectrum was measured as the applied load was increased. Good correlations (r > 0.96) between the measured load and the predicted load were obtained using spectra taken from both the tension and compression surfaces of the small wood beams.     

Flagging incorrect nucleotide sequence reagents in biomedical papers: To what extent does the leading publication format impede automatic error detection?

Scientometrics - In an idealised vision of science the scientific literature is error-free. Errors reported during peer review are supposed to be corrected prior to publication, as further research...     

Olaparib Is a Mitochondrial Complex I Inhibitor That Kills Temozolomide-Resistant Human Glioblastoma Cells

Glioblastoma represents the highest grade of brain tumors. Despite maximal resection surgery associated with radiotherapy and concomitant followed by adjuvant chemotherapy with temozolomide (TMZ), patients have a very poor prognosis due to the rapid recurrence and the acquisition of resistance to TMZ. Here, initially considering that TMZ is a prodrug whose activation is pH-dependent, we explored the contribution of glioblastoma cell metabolism to TMZ resistance. Using isogenic TMZ-sensitive and TMZ-resistant human glioblastoma cells, we report that the expression of O6-methylguanine DNA methyltransferase (MGMT), which is known to repair TMZ-induced DNA methylation, does not primarily account for TMZ resistance. Rather, fitter mitochondria in TMZ-resistant glioblastoma cells are a direct cause of chemoresistance that can be targeted by inhibiting oxidative phosphorylation and/or autophagy/mitophagy. Unexpectedly, we found that PARP inhibitor olaparib, but not talazoparib, is also a mitochondrial Complex I inhibitor. Hence, we propose that the anticancer activities of olaparib in glioblastoma and other cancer types combine DNA repair inhibition and impairment of cancer cell respiration.     

Engineered Extracellular Matrices as Biomaterials of Tunable Composition and Function

Engineered and decellularized extracellular matrices (ECM) are receiving increasing interest in regenerative medicine as materials capable to induce cell growth/differentiation and tissue repair by physiological presentation of embedded cues. However, ECM production/decellularization processes and control over their composition remain primary challenges. This study reports engineering of ECM materials with customized properties, based on genetic manipulation of immortalized and death‐inducible human mesenchymal stromal cells (hMSC), cultured within 3D porous scaffolds under perfusion flow. The strategy allows for robust ECM deposition and subsequent decellularization by deliberate cell‐apoptosis induction. As compared to standard production and freeze/thaw treatment, this grants superior preservation of ECM, leading to enhanced bone formation upon implantation in calvarial defects. Tunability of ECM composition and function is exemplified by modification of the cell line to overexpress vascular endothelial growth factor alpha (VEGF), which results in selective ECM enrichment and superior vasculature recruitment in an ectopic implantation model. hMSC lines culture under perfusion‐flow is pivotal to achieve uniform scaffold decoration with ECM and to streamline the different engineering/decellularization phases in a single environmental chamber. The findings outline the paradigm of combining suitable cell lines and bioreactor systems for generating ECM‐based off‐the‐shelf materials, with custom set of signals designed to activate endogenous regenerative processes.     

Observations on the zinc protoporphyrin/heme ratio in whole blood

The aim of this study was to examine whether severity of preoperative pain intensity is related to postoperative pain and morphine consumption. Sixty consecutive patients scheduled for total hip surgery during intrathecal anesthesia were studied. Preoperative visual analog scale (VAS) scores and analgesic intake was assessed 1 day before surgery. Three groups of patients were identified: those with mild pain (n = 12, VAS score 0-4), moderate pain (n = 18, VAS score 4-7), and severe pain (n = 28, VAS score 7-10). Postoperative pain scores were recorded in the first 24 h, as was the amount of morphine delivered by the patient-controlled analgesia pump. There were no differences among the groups in VAS scores at any time. Severe preoperative pain levels correlated with significantly greater postoperative morphine intake. The mean morphine intake during the first 24 h postoperatively was 19.2 mg in the mild pain group, 21.2 mg in the moderate pain group, and 29.5 mg in the severe pain group (P < 0.05 compared with both other groups). We conclude that patients with severe preoperative pain self-medicate to achieve postoperative pain scores equivalent to those of patients with mild and moderate pain and require a greater postoperative morphine intake for adequate analgesia than patients with mild or moderate preoperative pain. IMPLICATIONS: In this study, we showed that severity of preoperative pain intensity relates to postoperative pain levels and morphine consumption. Patients scheduled for total hip surgery with severe preoperative pain require more postoperative morphine in the first 24 h.     

On finite-element implementation strategies of Schapery-type constitutive theories

This paper presents two new strategies for implementing Schapery-type nonlinearly viscoelastic constitutive theories into finite element codes. The first strategy uses the original differential equations that lead to the integral formulation of Schapery-type constitutive theories and Finite Difference (FD) schemes. This strategy is quite different from all the other strategies found in the literature. The second strategy is an improvement of recursive strategies, used by many authors, based on the integral formulation of the constitutive theory. The performances of the new algorithms are compared with those of existing strategies for various load histories and nonlinearities. It is shown that the newly developed strategy based on FD schemes can exhibit quadratic convergence rate when one time step is stored and 4th order convergence rate when two time steps are stored, which is a major improvement over the recursive strategies.     

Excited States Computation of Models of Phenylalanine Protein Chains: TD-DFT and Composite CC2/TD-DFT Protocols

The present benchmark calculations testify to the validity of time-dependent density functional theory (TD-DFT) when exploring the low-lying excited states potential energy surfaces of models of phenylalanine protein chains. Among three functionals suitable for systems exhibiting charge-transfer excited states, LC-ωPBE, CAM-B3LYP, and ωB97X-D, which were tested on a reference peptide system, we selected the ωB97X-D functional, which gave the best results compared to the approximate coupled-cluster singles and doubles (CC2) method. A quantitative agreement for both the geometrical parameters and the vibrational frequencies was obtained for the lowest singlet excited state (a ππ* state) of the series of capped peptides. In contrast, only a qualitative agreement was met for the corresponding adiabatic zero-point vibrational energy (ZPVE)-corrected excitation energies. Two composite protocols combining CC2 and DFT/TD-DFT methods were then developed to improve these calculations. Both protocols substantially reduced the error compared to CC2 and experiment, and the best of both even led to results of CC2 quality at a lower cost, thus providing a reliable alternative to this method for very large systems.     

Small Molecule‐Based Fluorescent Organic Nanoassemblies with Strong Hydrogen Bonding Networks for Fine Tuning and Monitoring Drug Delivery in Cancer Cells

Bright supramolecular fluorescent organic nanoassemblies (FONs), based on strongly polar red‐emissive benzothiadiazole fluorophores containing acidic units, are fabricated to serve as theranostic tools with large colloidal stability in the absence of a polymer or surfactant. High architectural cohesion is ensured by the multiple hydrogen‐bonding networks, reinforced by the dipolar and hydrophobic interactions developed between the dyes. Such interactions are harnessed to ensure high payload encapsulation and efficient trapping of hydrophobic and hydrogen‐bonding drugs like doxorubicin, as shown by steady state and time‐resolved measurements. Fine tuning of the drug release in cancer cells is achieved by adjusting the structure and combination of the fluorophore acidic units. Notably delayed drug delivery is observed by confocal microscopy compared to the entrance of hydrosoluble doxorubicin, demonstrating the absence of undesirable burst release outside the cells by using FONs. Since FON‐constituting fluorophores exhibit a large emission shift from red to green when dissociating in contact with the lipid cellular content, drug delivery could advantageously be followed by dual‐color spectral detection, independently of the drug staining potentiality.     

Comparison Between Robust and Stochastic Optimisation for Long-term Reservoir Management Under Uncertainty

Long-term reservoir management often uses bounds on the reservoir level, between which the operator can work. However, these bounds are not always kept up-to-date with the latest knowledge about the reservoir drainage area, and thus become obsolete. The main difficulty with bounds computation is to correctly take into account the high uncertainty about the inflows to the reservoir. In this article, we propose a methodology to derive minimum bounds while providing formal guarantees about the quality of the obtained solutions. The uncertainty is embedded using either stochastic or robust programming in a model-predictive-control framework. We compare the two paradigms to the existing solution for a case study and find that the obtained solutions vary substantially. By combining the stochastic and the robust approaches, we also assign a confidence level to the solutions obtained by stochastic programming. The proposed methodology is found to be both efficient and easy to implement. It relies on sound mathematical principles, ensuring that a global optimum is reached in all cases.