Explore the vast range of titles available.

Purpose: The purpose of this work was to evaluate the potential of substituting autogenous bone (AB) by bone marrow aspirate concentrate (BMAC). Both AB and BMAC were tested in combination with a bovine bone mineral (BBM) for their ability of new bone formation (NBF) in a multicentric, randomized, controlled, clinical and histological noninferiority trial. Materials and Methods: Forty-five severely atrophied maxillary sinus from 26 patients were evaluated in a partial cross-over design. As test arm, 34 sinus of 25 patients were augmented with BBM and BMAC containing mesenchymal stem cells. Eleven control sinus from 11 patients were augmented with a mixture of 70% BBM and 30% AB. Biopsies were obtained after a 3–4-month healing period at time of implant placement and histomorphometrically analyzed for NBF. Results: NBF was 14.3%±1.8% for the control and nonsignificantly lower (12.6%±1.7%) for the test (90% confidence interval: −4.6 to 1.2). Values for BBM (31.3%±2.7%) were significantly higher for the test compared with control (19.3%±2.5%) (p<0.0001). Nonmineralized tissue was lower by 3.3% in the test compared with control (57.6%; p=0.137). Conclusions: NBF after 3–4 months is equivalent in sinus, augmented with BMAC and BBM or a mixture of AB and BBM. This technique could be an alternative for using autografts to stimulate bone formation.

We perform a comprehensive analysis of the quantum-enhanced Monte Carlo method [Nature, 619, 282-287 (2023)], aimed at identifying the optimal working point of the algorithm. We observe an optimal mixing Hamiltonian strength and analyze the scaling of the total evolution time with the size of the system. We also explore extensions of the circuit, including the use of time-dependent Hamiltonians and reverse digitized annealing. Additionally, we propose that classical, approximate quantum simulators can be used for the proposal step instead of the original real-hardware implementation. We observe that tensor-network simulators, even with unconverged settings, can maintain a scaling advantage over standard classical samplers. This may extend the utility of quantum-enhanced Monte Carlo as a quantum-inspired algorithm, even before the deployment of large-scale quantum hardware.

We perform a comprehensive analysis of the quantum-enhanced Monte Carlo method [Nature, 619, 282-287 (2023)], aimed at identifying the optimal working point of the algorithm. We observe an optimal mixing Hamiltonian strength and analyze the scaling of the total evolution time with the size of the system. We also explore extensions of the circuit, including the use of time-dependent Hamiltonians and reverse digitized annealing. Additionally, we propose that classical, approximate quantum simulators can be used for the proposal step instead of the original real-hardware implementation. We observe that tensor-network simulators, even with unconverged settings, can maintain a scaling advantage over standard classical samplers. This may extend the utility of quantum enhanced Monte Carlo as a quantum-inspired algorithm, even before the deployment of large-scale quantum hardware.

To advance the technology of polymer electrolyte membrane fuel cells, material development is at the forefront of research. This is especially true for membrane electrode assembly, where the structuring of its various layers has proven to be directly linked to performance increase. In this study, we investigate the influence of the various ingredients in the cathode catalyst layer, such as ionomer content, catalyst loading and catalyst type, on the oxygen and ion transport using a full parametric analysis. Using two types of catalysts, 40 wt.% Pt/C and 60 wt.% Pt/C with high surface area carbon, the ionomer/carbon content was varied between 0.29–1.67, while varying the Pt loading in the range of 0.05–0.8 mg cm−2. The optimum ionomer content was found to be dependent on the operating point and condition, as well as catalyst loading and type. The data set provided in this work gives a starting point to further understanding of structured catalyst layers.

Psoriasis is one of the most common immune-mediated inflammatory skin diseases. Expression and secretion of two pro-inflammatory molecules of the S100-alarmin family, S100A8 and S100A9, in keratinocytes is a hallmark of psoriasis, which is also characterized by an altered differentiation of keratinocytes. Dimers of S100A8/S100A9 (calprotectin) bind to Toll-like receptor 4 and induce an inflammatory response in target cells. Targeted deletion of S100A9 reduced the inflammatory phenotype of psoriasis-like inflammation in mice. A role of S100-alarmins in differentiation and activation of keratinocytes was suggested but has been never shown in primary keratinocytes. We now confirm that induction of S100-alarmins in an imiquimod-induced murine model of psoriasis-like skin inflammation was associated with an increased expression of interleukin (IL)-1α, IL-6, IL-17A, or TNFα. This association was confirmed in transcriptome data obtained from controls, lesional and non-lesional skin of psoriasis patients, and a down-regulation of S100-alarmin expression after IL-17 directed therapy. However, analyzing primary S100A9 −/− keratinocytes we found that expression of S100A8/S100A9 has no significant role for the maturation and inflammatory response pattern of keratinocytes. Moreover, keratinocytes are no target cells for the pro-inflammatory effects of S100A8/S100A9. However, different cytokines, especially IL-17A and F, highly abundant in psoriasis, strongly induced expression of S100-alarmins preferentially during early maturation stages of keratinocytes. Our data indicate that expression of S100A8 and S100A9 does not primarily influence maturation or activation of keratinocytes but rather represents the inflammatory response of these cells during psoriasis.

We present the result of the third Marine Ice Sheet Model Intercomparison Project, MISMIP+. MISMIP+ is intended to be a benchmark for ice-flow models which include fast sliding marine ice streams and floating ice shelves and in particular a treatment of viscous stress that is sufficient to model buttressing, where upstream ice flow is restrained by a downstream ice shelf. A set of idealized experiments first tests that models are able to maintain a steady state with the grounding line located on a retrograde slope due to buttressing and then explore scenarios where a reduction in that buttressing causes ice stream acceleration, thinning, and grounding line retreat. The majority of participating models passed the first test and then produced similar responses to the loss of buttressing. We find that the most important distinction between models in this particular type of simulation is in the treatment of sliding at the bed, with other distinctions – notably the difference between the simpler and more complete treatments of englacial stress but also the differences between numerical methods – taking a secondary role.

For crystalline-silicon solar cells, voltages close to the theoretical limit are nowadays readily achievable when using passivating contacts. Conversely, maximal current generation requires the integration of the electron and hole contacts at the back of the solar cell to liberate its front from any shadowing loss. Recently, the world-record efficiency for crystalline-silicon single-junction solar cells was achieved by merging these two approaches in a single device; however, the complexity of fabricating this class of devices raises concerns about their commercial potential. Here we show a contacting method that substantially simplifies the architecture and fabrication of back-contacted silicon solar cells. We exploit the surface-dependent growth of silicon thin films, deposited by plasma processes, to eliminate the patterning of one of the doped carrier-collecting layers. Then, using only one alignment step for electrode definition, we fabricate a proof-of-concept 9-cm 2 tunnel-interdigitated back-contact solar cell with a certified conversion efficiency >22.5%. The most efficient silicon solar cells use interdigitated back-contact silicon heterojunction architectures. Here, the authors fabricate this type of cell via a simpler process, using an interband silicon tunnel junction for the electron contact and reaching a certified efficiency higher than 22%.

Urban-living individuals are exposed to many environmental factors that may combine and interact to influence mental health. While individual factors of an urban environment have been investigated in isolation, no attempt has been made to model how complex, real-life exposure to living in the city relates to brain and mental health, and how this is moderated by genetic factors. Using the data of 156,075 participants from the UK Biobank, we carried out sparse canonical correlation analyses to investigate the relationships between urban environments and psychiatric symptoms. We found an environmental profile of social deprivation, air pollution, street network and urban land-use density that was positively correlated with an affective symptom group ( r  = 0.22, P perm  < 0.001), mediated by brain volume differences consistent with reward processing, and moderated by genes enriched for stress response, including CRHR1 , explaining 2.01% of the variance in brain volume differences. Protective factors such as greenness and generous destination accessibility were negatively correlated with an anxiety symptom group ( r  = 0.10, P perm  < 0.001), mediated by brain regions necessary for emotion regulation and moderated by EXD3 , explaining 1.65% of the variance. The third urban environmental profile was correlated with an emotional instability symptom group ( r  = 0.03, P perm  < 0.001). Our findings suggest that different environmental profiles of urban living may influence specific psychiatric symptom groups through distinct neurobiological pathways. Analyses of data from the UK Biobank reveal different urban living environments that are associated with affective, anxiety and emotional instability symptom groups and mediated by distinct neurological and genetic pathways in adults.

Background: In a post-hoc analysis of a pediatric asthma study, we identified the predictors of asthma exacerbations (AEs) and related them to forced expiratory volume (FEV 1 ), the FEV 1 /FVC ratio, and bronchial hyperresponsiveness (BHR). Objectives: We sought to detect predictors of AEs in a prospective study that utilizes impulse oscillometry (IOS) and to compare the results to previously determined predictors. Methods: A moderate AE was defined as an increased use of salbutamol during coughing episodes. Pulmonary function and BHR were measured during symptom- and medication-free periods. Additionally, allergen testing and IOS were included. To calculate the sensitivity and specificity of AE detection, a receiver-operating characteristic (ROC) curve was plotted, and accuracy was measured with the area under the ROC curve (AUC). A logistic regression analysis was used to predict the probability of an exacerbation. Results: Seventy-five pediatric patients (4-7 years of age) with intermittent asthma were included. In 69 patients, the following cut-off values demonstrated the best sensitivity and specificity combination for predicting an AE: FEV 1 103.2% (AUC 0.62), BHR (PD 20 methacholine) 0.13 mg (AUC 0.61), and, in 54 children, Rrs5 0.78 kPa × l -1 × s (AUC 0.80). Logistic regression analysis demonstrated that the combination of all parameters predicted the individual risk of AEs with an accuracy of 86%. Conclusions: IOS, a simple method, predicted the probability of AEs in young children. Airway resistance, measured by IOS, was superior to FEV 1 and methacholine testing. The current data suggest that peripheral airway obstruction is present during symptom-free periods and that these children more likely experience AEs.

Preterm infants are at significant risk to develop reduced bone mineralization based on inadequate supply of calcium and phosphorus (Ca-P). Biochemical parameters can be used to evaluate the nutritional intake. The direct effect of nutritional intake on changes in biochemical parameters has not been studied. Our objective was to evaluate the effect of Ca-P supplementation on biochemical markers as serum (s)/urinary (u) Ca and P; alkaline phosphatase (ALP); tubular reabsorption of P (TrP); and urinary ratios for Ca/creatinin (creat) and P/creatinin in Very-Low-Birth-Weight infants on Postnatal Days 1, 3, 5, 7, 10, and 14. This observational study compared two groups with High (n = 30) and Low (n = 40) intake of Ca-P. Birth weight: median (IRQ) 948 (772–1225) vs. 939 (776–1163) grams; and gestational age: 28.2 (26.5–29.6) vs. 27.8 (26.1–29.4) weeks. Daily median concentrations of biochemical parameter were not different between the groups but linear regression mixed model analyses showed that Ca intake increased the uCa and TrP (p = 0.04) and decreased ALP (p = 0.00). Phosphorus intake increased sP, uP and uP/creat ratio and ALP (p ≤ 0.02) and caused decrease in TrP (p = 0.00). Protein intake decreased sP (p = 0.000), while low gestational age and male gender increased renal excretion of P (p < 0.03). Standardized repeated measurements showed that biochemical parameters were affected by nutritional intake, gestational age and gender.