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To comprehensively assess osteoporosis in the lumbar spine, a compositional MR imaging technique is proposed to quantify proton fractions for all the water components as well as fat in lumbar vertebrae measured by a combination of a 3D short repetition time adiabatic inversion recovery prepared ultrashort echo time (STAIR-UTE) MRI and IDEAL-IQ.A total of 182 participants underwent MRI, quantitative CT, and DXA. Lumbar collagen-bound water proton fraction (CBWPF), free water proton fraction (FWPF), total water proton fraction (TWPF), bone mineral density (BMD), and T-score were calculated in three vertebrae (L2-L4) for each subject. The correlations of the CBWPF, FWPF, and TWPF with BMD and T-score were investigated respectively. A comprehensive diagnostic model combining all the water components and clinical characteristics was established. The performances of all the water components and the comprehensive diagnostic model to discriminate between normal, osteopenia, and osteoporosis cohorts were also evaluated using receiver operator characteristic (ROC).The CBWPF showed strong correlations with BMD (r = 0.85, p0.001) and T-score (r = 0.72, p0.001), while the FWPF and TWPF showed moderate correlations with BMD (r = 0.65 and 0.68, p0.001) and T-score (r = 0.47 and 0.49, p0.001). The high area under the curve values obtained from ROC analysis demonstrated that CBWPF, FWPF, and TWPF have the potential to differentiate the normal, osteopenia, and osteoporosis cohorts. At the same time, the comprehensive diagnostic model shows the best performance.The compositional MRI technique, which quantifies CBWPF, FWPF, and TWPF in trabecular bone, is promising in the assessment of bone quality.• Compositional MR imaging technique is able to quantify proton fractions for all the water components (i.e., collagen-bound water proton fraction (CBWPF), free water proton fraction (FWPF), and total water proton fraction (TWPF)) in the human lumbar spine. • The biomarkers derived from the compositional MR imaging technique showed moderate to high correlations with bone mineral density (BMD) and T-score and showed good performance in distinguishing people with different bone mass. • The comprehensive diagnostic model incorporating CBWPF, FWPF, TWPF, and clinical characteristics showed the highest clinical diagnostic capability for the assessment of osteoporosis.

To improve the efficiency and accuracy of single-event effect (SEE) research at the Heavy Ion Research Facility at Lanzhou, Hi’Beam-SEE must precisely localize the position at which each heavy ion hitting the integrated circuit (IC) causes SEE. In this study, we propose a fast multi-track location (FML) method based on deep learning to locate the position of each particle track with high speed and accuracy. FML can process a vast amount of data supplied by Hi’Beam-SEE online, revealing sensitive areas in real time. FML is a slot-based object-centric encoder–decoder structure in which each slot can learn the location information of each track in the image. To make the method more accurate for real data, we designed an algorithm to generate a simulated dataset with a distribution similar to that of the real data, which was then used to train the model. Extensive comparison experiments demonstrated that the FML method, which has the best performance on simulated datasets, has high accuracy on real datasets as well. In particular, FML can reach 238 fps and a standard error of 1.6237 μm. This study discusses the design and performance of FML.

Bone collagen matrix makes a crucial contribution to the mechanical properties of bone by imparting tensile strength and elasticity. The collagen content of bone is accessibleA total of 189 participants with a mean age of 56 (ranged from 50 to 86) years old were underwent MRI, quantitative computed tomography (QCT), and dual-energy X-ray absorptiometry (DXA) in lumbar spine. Major fracture risk was also evaluated for all participants using Fracture Risk Assessment Tool (FRAX). Lumbar CBWPD, bone marrow fat fraction (BMFF), bone mineral density (BMD) and T score values were calculated in three vertebrae (L2-L4) for each subject. Both the CBWPD and BMFF were correlated with BMD, T score, and FRAX score for comparison. The abilities of the CBWPD and BMFF to discriminate between three different cohorts, which included normal subjects, patients with osteopenia, and patients with osteoporosis, were also evaluated and compared using receiver operator characteristic (ROC) analysis.The CBWPD showed strong correlation with standard BMD (RThe STAIR-UTE-measured CBWPD is a promising biomarker in the assessment of bone quality and fracture risk.

Efficient detection of stealthy malware attacks in suspicious files is very challenging as dynamic malware analysis is time consuming. This paper proposes a virtual time control mechanics-based method to overcome the challenge. The proposed method utilizes a modified Xen hypervisor, in which a virtual clock source is generated according to a predefined speed ratio, such that sandbox systems running on the modified hypervisor can be accelerated. Thus, it does not modify operating system kernels nor intercept system function calls, and is therefore compatible with various operating systems. Further, it utilizes an entropy-based measure that adjusts its execution time according to various malware inputs as an early termination criterion. The results of experiments conducted to verify the efficacy of the proposed method indicate that it speeds up the system timer and significantly increases the logged record size by up to 42% or obtains the same log size within a shorter period compared with conventional sandboxes. Thus, the proposed virtual time control mechanics-based method efficiently detects nontrivial anomalous codes that may be neglected by conventional sandboxing techniques.

Blockchain has flourished in recent years. As a decentralized system architecture, smart contracts give the blockchain a user-defined logical concept. The smart contract is an executable program that can be used for automatic transactions on the Ethereum blockchain. In 2016, the DAO attack resulted in the theft of 60M USD due to unsafe smart contracts. Smart contracts are vulnerable to hacking because they are difficult to patch and there is a lack of assessment standards for ensuring their quality. Hackers can exploit the vulnerabilities in smart contracts when they have been published on Ethereum. Thus, this study presents SoliAudit (Solidity Audit), which uses machine learning and fuzz testing for smart contract vulnerability assessment. SoliAudit employs machine learning technology using Solidity machine code as learning features to verify 13 kinds of vulnerabilities, which have been listed as Top 10 threats by an open security organization. We also created a gray-box fuzz testing mechanism, which consists of a fuzzer contract and a simulated blockchain environment for on-line transaction verification. Different from previous research systems, SoliAudit can detect vulnerabilities without expert knowledge or predefined patterns. We subjected SoliAudit to real-world evaluation by using near 18k smart contracts from the Ethereum blockchain and Capture-the-Flag samples. The results show that the accuracy of SoliAudit can reach to 90% and the fuzzing can help identify potential weaknesses, including reentrancy and arithmetic overflow problems.

Indan and 1,3-benzodioxole groups were introduced to the central pyrrole ring of the dithienylpyrrole-based conducting polymers backbone, which are denominated as PIND and PMDOB, respectively. The two series of dithienylpyrrole-based polymers were electrochemically synthesized, and the cyclic voltammograms showed the redox properties of electrochemically prepared films deposited at various scan rates. Spectroelectrochemical investigations conducted in this study showed that PIND and PMDOB films are yellowish-green and yellow color, respectively, in the neutral state; they can be reversibly oxidized and reduced and this is accompanied by obvious color changes. Maximum optical contrast (Δ T max ) of the P(IND-co-perylene) s and P(MDOB-co-perylene) s films were measured as 60.7 % at 932 nm and 64.8 % at 962 nm, respectively, in an ionic liquid solution, and the maximum coloration efficiency ( η ) of P(IND-co-perylene)s and P(MDOB-co-perylene)s films were calculated to be 199.2 and 209.7 cm 2 C −1 , respectively, in an ionic liquid solution. Electrochromic devices (ECD) based on PIND and PMDOB as anodic polymers and poly(3,4-(2,2-diethylpropylenedioxy) thiophene) (PProDOT-Et 2 ) as cathodic polymer were constructed. PIND/PProDOT-Et 2 ECD showed a high Δ T max (33.1%) at 582 nm and satisfactory redox stability, whereas PMDOB/PProDOT-Et 2 ECD showed a high coloration efficiency (375.9 cm 2 C −1 ) and satisfactory optical memories.

Background: Clostridium difficile infection (CDI) is a significant cause of morbidity and mortality in both the acute care setting and the wider healthcare system. The purpose of this study was to evaluate the in vitro activity of fidaxomicin against C. difficile isolates from a university teaching hospital in China. Methods: One hundred and one C. difficile isolates were collected and analyzed for toxin genes by multiplex PCR. The toxin gene positive strains were also typed by multilocus sequence typing (MLST) and PCR-ribotyping. The MICs of the isolates were determined against fidaxomicin, metronidazole, vancomycin, tigecycline and moxifloxacin, by the agar dilution method. Results: All the 101 isolates exhibited low MICs to fidaxomicin (0.032–1 mg/L), metronidazole (0.125–1 mg/L), vancomycin (0.25–2 mg/L) and tigecycline (0.016–0.5 mg/L). Tigecycline showed the lowest geometric mean MIC value (0.041 mg/L), followed by fidaxomicin (0.227 mg/L), metronidazole (0.345 mg/L), and vancomycin (0.579 mg/L). About 35% of the strains (n = 35) were resistant to moxifloxacin, and the resistance rate to moxifloxacin for A−B+CDT− isolates (85.0%) was much higher than that of A+B+CDT− (15.7%) and A−B−CDT− (29.2%) isolates (P

Colorectal cancer (CRC) is a common neoplastic disease and a frequent cause of death. Drug resistance is a major challenge to CRC treatment and stem-like side-population (SP) cells may play a key role in this resistance. Although it has been recognized that cancer stem cells may be affected by redox status, the underlying mechanisms for this effect and the roles of celllular redox adaptation and antioxidant capacity in CRC remain elusive. Our study shows that CRC SP cells are highly dependent on cellular GSH to maintain ROS levels below those of non-SP cells. Exposing CRC cells to H2O2 produced a significant decrease in the percentage of SP cells, which was rescued by adding N-acetylcysteine. Mechanistically, CD44v interacts with and stabilizes xCT and thereby promotes the uptake of cysteine for GSH synthesis and stimulates SP cell enrichment. Additionally, miR-1297 levels were inversely correlated with the expression of xCT; thus, reduced miR-1297 contributes to SP cell enrichment in CRC tumors, which results in tumor aggressiveness and poor clinical outcomes. Importantly, redox modification by PEITC significantly reduces CRC SP cells in vitro and impairs tumors growth in vivo. The combination of 5FU and PEITC led to synergistic cytotoxic effects against CRC cells in vitro and in vivo. Taken together, our data suggest that a GSH-mediated reduction in cellular ROS levels is an essential regulator of CRC SP cells mediated by the CD44v-xCT axis, and disrupting the redox status may eliminate the chemotherapy-resistant CRC SP cells with potentially significant benefits for cancer treatment.