Multi-contrast brain magnetic resonance image super-resolution using the local weight similarity

Abstract Background Low-resolution images may be acquired in magnetic resonance imaging (MRI) due to limited data acquisition time or other physical constraints, and their resolutions can be improved with super-resolution methods. Since MRI can offer images of an object with different contrasts, e.g., T1-weighted or T2-weighted, the shared information between inter-contrast images can be used to benefit super-resolution. Methods In this study, an MRI image super-resolution approach to enhance in-plane resolution is proposed by exploring the statistical information estimated from another contrast MRI image that shares similar anatomical structures. We assume some edge structures are shown both in T1-weighted and T2-weighted MRI brain images acquired of the same subject, and the proposed approach aims to recover such kind of structures to generate a high-resolution image from its low-resolution counterpart. Results The statistical information produces a local weight of image that are found to be nearly invariant to the image contrast and thus this weight can be used to transfer the shared information from one contrast to another. We analyze this property with comprehensive mathematics as well as numerical experiments. Conclusion Experimental results demonstrate that the image quality of low-resolution images can be remarkably improved with the proposed method if this weight is borrowed from a high resolution image with another contrast. Graphical Abstract Multi-contrast MRI Image Super-resolution with Contrast-invariant Regression Weight

A columnar regular-porous stainless steel reaction support with high superficial area for hydrogen production

To improve hydrogen production (HP) performance of regular-porous structure (RPS), a columnar RPS with small specific surface area and high superficial area is developed. A numerical simulation model of regular-porous stainless steel structure (RPSSS) is established. Subsequently, heat transfer performance, pressure loss, temperature, methanol concentration, H2 concentration distributions and HP performance of the columnar RPSSS with small specific surface area and high superficial area and the body-centered cubic RPSSS with high specific surface area and small superficial area are compared. Then, temperature, methanol concentration, H2 concentration distributions and HP performance of axial and longitudinal size-enlarged columnar RPSSSs are studied. The results show that compared to the body-centered cubic RPSSS, the columnar RPSSS has higher methanol conversion, larger H2 flow rate and higher CO selectivity. Especially in the condition of 300 °C wall temperature and 12 mL/h methanol-water mixture injection rate (MWMIR), the methanol conversion, H2 flow rate and CO selectivity of the columnar RPSSS are increased by 12.3%, 9.24% and 30%, respectively, indicating that the superficial area of RPSSS is more important for its HP performance compared to its specific surface area. Compared to the longitudinal size-enlarged columnar RPSSS, the axial size-enlarged columnar RPSSS has higher methanol conversion, larger H2 flow rate and higher CO selectivity. This research work provides a new method for the optimization of hydrogen production reaction support (HPRS)

Pharmacokinetics/pharmacodynamics of polymyxin B in patients with bloodstream infection caused by carbapenem-resistant Klebsiella pneumoniae

Introduction: Polymyxin B is a last-line therapy for carbapenem-resistant microorganisms. However, a lack of clinical pharmacokinetic/pharmacodynamic (PK/PD) data has substantially hindered dose optimization and breakpoint setting.Methods: A prospective, multi-center clinical trial was undertaken with polymyxin B [2.5 mg/kg loading dose (3-h infusion), 1.25 mg/kg/12 h maintenance dose (2-h infusion)] for treatment of carbapenem-resistant K. pneumoniae (CRKP) bloodstream infections (BSI). Safety, clinical and microbiological efficacy were evaluated. A validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was applied to determine the concentrations of polymyxin B in blood samples. Population pharmacokinetic (PK) modeling and Monte Carlo simulations were conducted to examine the susceptibility breakpoint for polymyxin B against BSI caused by CRKP.Results: Nine patients were enrolled and evaluated for safety. Neurotoxicity (5/9), nephrotoxicity (5/9), and hyperpigmentation (1/9) were recorded. Blood cultures were negative within 3 days of commencing therapy in all 8 patients evaluated for microbiological efficacy, and clinical cure or improvement occurred in 6 of 8 patients. Cmax and Cmin following the loading dose were 5.53 ± 1.80 and 1.62 ± 0.41 mg/L, respectively. With maintenance dosing, AUCss,24 h was 79.6 ± 25.0 mg h/L and Css,avg 3.35 ± 1.06 mg/L. Monte Carlo simulations indicated that a 1 mg/kg/12-hourly maintenance dose could achieve >90% probability of target attainment (PTA) for isolates with minimum inhibitory concentration (MIC) ≤1 mg/L. PTA dropped substantially for MICs ≥2 mg/L, even with a maximally recommended daily dose of 1.5 mg/kg/12-hourly.Conclusion: This is the first clinical PK/PD study evaluating polymyxin B for BSI. These results will assist to optimize polymyxin B therapy and establish its breakpoints for CRKP BSI

Summer Outdoor Thermal Comfort in Urban Commercial Pedestrian Streets in Severe Cold Regions of China

This paper investigates outdoor thermal comfort in summer in commercial pedestrian streets in Harbin, using meteorological measurements and questionnaire surveys (1013 valid questionnaires). The results demonstrate that: (1) Thermal sensation has a lower range in an outdoor environment with smaller sky view factor (SVF) and less fluctuation, while the thermal sensation vote (TSV) range is more dispersed in an outdoor environment with larger SVF and more fluctuation; (2) In the urban, high-density commercial districts in Harbin, the air temperature and solar radiation have a greater influence on outdoor thermal sensation, while wind speed has less of an influence, and residents in areas with less fluctuations are more sensitive to air temperature and solar radiation; (3) The universal thermal climate index (UTCI) can accurately evaluate outdoor thermal comfort in Harbin in summer, with a neutral UTCI value of 19.3 °C and a range from 15.6 to 23.0 °C; (4) The actual acceptable thermal range is 16.8–29.3 °C, and this takes into account the psychological adaptation of the residents, which provides a more practical reference value; (5) With reference to the psychological adaptation, the outdoor thermal sensation of residents in early summer is about 0.5 TSV higher than that in late summer. These results provide a theoretical basis and a technical reference for the design of commercial pedestrian streets in severe cold regions

Hyperspectral Pansharpening With Adaptive Feature Modulation-Based Detail Injection Network

International audienceRecently, deep learning-based methodologies have attained unprecedented performance in hyperspectral (HS) pansharpening, which aims to improve the spatial quality of HS images (HSIs) by making use of details extracted from the high-resolution panchromatic (HR-PAN) image. However, it remains challenging to incorporate the details into the pansharpened image effectively, while alleviating the spectral distortion simultaneously. To tackle this problem, in this article, we propose an adaptive feature modulation-based detail injection network (AFM-DIN) for HS pansharpening, which mainly consists of four phases: high-frequency details generation of the HR-PAN image, multiscale feature extraction of the upsampled HSI, AFM-based detail injection, and reconstruction of the HR-HSI. First, a novel octave convolution unit is employed to decompose the HR-PAN image into high and low frequencies, and then merge the high-frequency features together to generate the comprehensive PAN-details. Second, the spatial and spectral separable 3-D convolution units with multiple kernel sizes are designed to extract multiscale features of the upsampled HSI in a computationally efficient manner. Subsequently, by taking the critical PAN-details as prior, the proposed AFM module is able to not only incorporate the detail information effectively, but also adjust the injected details adaptively to ensure the spectral fidelity. Finally, the anticipated HR-HSI is obtained through adding the upsampled HSI to the predicted HSI-details reconstructed from informative modulated features. Extensive comparison experiments with several state-of-the-arts conducted on simulated and real HS data sets demonstrate that our proposed AFM-DIN can achieve superior pansharpening accuracy in both spatial and spectral aspects

Hyperspectral Pansharpening With Adaptive Feature Modulation-Based Detail Injection Network

International audienceRecently, deep learning-based methodologies have attained unprecedented performance in hyperspectral (HS) pansharpening, which aims to improve the spatial quality of HS images (HSIs) by making use of details extracted from the high-resolution panchromatic (HR-PAN) image. However, it remains challenging to incorporate the details into the pansharpened image effectively, while alleviating the spectral distortion simultaneously. To tackle this problem, in this article, we propose an adaptive feature modulation-based detail injection network (AFM-DIN) for HS pansharpening, which mainly consists of four phases: high-frequency details generation of the HR-PAN image, multiscale feature extraction of the upsampled HSI, AFM-based detail injection, and reconstruction of the HR-HSI. First, a novel octave convolution unit is employed to decompose the HR-PAN image into high and low frequencies, and then merge the high-frequency features together to generate the comprehensive PAN-details. Second, the spatial and spectral separable 3-D convolution units with multiple kernel sizes are designed to extract multiscale features of the upsampled HSI in a computationally efficient manner. Subsequently, by taking the critical PAN-details as prior, the proposed AFM module is able to not only incorporate the detail information effectively, but also adjust the injected details adaptively to ensure the spectral fidelity. Finally, the anticipated HR-HSI is obtained through adding the upsampled HSI to the predicted HSI-details reconstructed from informative modulated features. Extensive comparison experiments with several state-of-the-arts conducted on simulated and real HS data sets demonstrate that our proposed AFM-DIN can achieve superior pansharpening accuracy in both spatial and spectral aspects

Hyperspectral Pansharpening Using Deep Prior and Dual Attention Residual Network

International audienceConvolutional neural networks (CNNs) have recently achieved impressive improvements on hyperspectral (HS) pansharpening. However, most of the CNN-based HS pansharpening approaches would have to first upsample the low-resolution hyperspectral image (LR-HSI) using bicubic interpolation or data-driven training strategy, which inevitably lose some details or greatly rely on the learning process. In addition, most previous methods regard the pansharpening as a black-box problem and treat diverse features equally, thus hindering the discriminative ability of CNNs. To conquer these issues, a novel HS pansharpening method using deep hyperspectral prior (DHP) and dual-attention residual network (DARN) is proposed in this article. Specifically, we first upsample the LR-HSI to the scale of the panchromatic (PAN) image through the DHP algorithm, which can better preserve spatial and spectral information without learning from large data sets. The upsampled result is then concatenated with the PAN image to form the input of the DARN, where several channel-spatial attention residual blocks (CSA ResBlocks) are stacked to map the residual HSI between the reference HSI and the upsampled HSI. In each CSA ResBlock, two complementary attention modules, i.e., channel attention and spatial attention modules, are designed to adaptively learn more informative features of spectral channels and spatial locations simultaneously, which can effectively boost the fusion accuracy. Finally, the fused HSI is obtained by the summation of the upsampled HSI and the reconstructed residual HSI. The experimental results of both simulated and real HS data sets demonstrate that the performance of our DHP-DARN method is superior over the state-of-the-art HS pansharpening approaches

Hypoxia-Induced Upregulation of HE4 Is Responsible for Resistance to Radiation Therapy of Gastric Cancer

Upregulation of human epididymis protein 4 (HE4) is often observed in different types of cancers, including gastric cancer (GC), but the association of elevated HE4 level with radiation resistance in GC remains unclear. The expression of HE4 and hypoxia-inducible factor 1α subunit (HIF1α) was assessed in GC patient samples and cell lines. Chromatin immunoprecipitation (ChIP) and luciferase reporter assays were performed to reveal the regulation between HE4 and HIF1α. Stable HE4 knockdown and HIF1α overexpression were introduced into GC cell lines to study the role of HE4 in the resistance of GC to radiation therapy. Colony formation assay and the xenograft mouse model were used to investigate the effects of radiation on GC cells. HE4 and HIF1α were upregulated in both GC patient tissues and GC cells. Hypoxia and HIF1α upregulated HE4 by directly targeting the hypoxia response element in its promoter region. Stable HE4 knockdown significantly sensitized GC cells and xenograft tumors to radiation. HIF1α overexpression markedly elevated the radiation resistance of GC cells, which was almost completely abolished by HE4 knockdown. Hypoxia-induced upregulation of HE4 is responsible for resistance to radiation therapy of GC, suggesting that HE4 knockdown or inhibition, combined with radiation therapy, holds great potential in the clinical treatment of GC. Keywords: hypoxia, human epididymis protein 4, WFDC2, radiation therapy, gastric cancer, hypoxia-inducible factor 1 α subunit, HIF1α, resistanc

Effect of Sn doping concentration on the oxidation of Al-containing MAX phase (Ti3AlC2) combining simulation with experiment

Sn doping is usually adopted to prepare Ti3AlC2 in mass production because it can reduce the synthesis temperature while increasing the phase purity. However, excessive Sn doping usually deteriorates the oxidation resistance of Ti3AlC2. Therefore, an appropriate Sn doping concentration is a vital issue. In this work, the effect of Sn doping concentration on the oxidation behavior of Ti3AlC2 was systematically investigated by combining theoretical calculations and experimental methods. Density function theory calculations suggest that the oxygen adsorption mechanisms for the (001) surface of Ti3AlC2 with and without Sn doping are similar, and Ti-O bonds are always preferentially formed. The molecular dynamics simulation further indicates that Al atoms have a faster diffusion rate during the oxidation process. Therefore, a continuous Al2O3 layer can form rapidly at high temperature. Nevertheless, when the Sn doping concentration exceeds 10 mol%, the continuity of the Al2O3 layer is destroyed, thereby impairing the oxidation resistance of Ti3AlC2. Furthermore, oxidation experiments verify the above results. The oxidation mechanisms of Ti3AlC2 with different Sn doping concentrations are also proposed