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Yunfei Zhang,1,2,&ast; Ruofan Sheng,1,2,&ast; Chun Yang,2 Yongming Dai,3 Mengsu Zeng1,2 1Shanghai Institute of Medical Imaging, Fudan University, Shanghai, 200032, People’s Republic of China; 2Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, People’s Republic of China; 3School of Biomedical Engineering, ShanghaiTech University, Shanghai, 200032, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yongming Dai, School of Biomedical Engineering, ShanghaiTech University, Shanghai, 200032, People’s Republic of China, Tel +86 13917166155, Email daiyongming5555@163.com Mengsu Zeng, Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, People’s Republic of China, Tel +86-021-64041990, Email zengmengsu111@163.comPurpose: To assess the effectiveness of tri-exponential Intra-Voxel Incoherent Motion (tri-IVIM) MRI in preoperatively identifying microvascular invasion (MVI) in hepatocellular carcinoma (HCC).Patients and Methods: In this prospective study, 67 patients with HCC were included. Metrics from bi-exponential IVIM (bi-IVIM) and tri-IVIM were calculated. Subgroup comparisons were analyzed using the independent Student’s t-test or Mann–Whitney U-test. Logistic regression was performed to explore clinical risk factors. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis.Results: MVI-positive HCCs exhibited significantly lower true diffusion coefficient (Dt) from bi-IVIM, as well as fast-diffusion coefficients (Df) and slow-diffusion coefficients (Ds) from tri-IVIM, compared to MVI-negative HCCs (p < 0.05). Tumor size and alpha-fetoprotein (AFP) were identified as risk factors. The combination of tri-IVIM-derived metrics (Ds and Df) yielded higher diagnostic accuracy (AUC = 0.808) compared to bi-IVIM (AUC = 0.741). A predictive model based on a nomogram was constructed using Ds, Df, tumor size, and AFP, resulting in the highest diagnostic accuracy (AUC = 0.859). Decision curve analysis indicated that the constructed model, provided the highest net benefit by accurately stratifying the risk of MVI, followed by tri-IVIM and bi-IVIM.Conclusion: Tri-IVIM can provide information on perfusion and diffusion for evaluating MVI in HCC. Additionally, tri-IVIM outperformed bi-IVIM in identifying MVI-positive HCC. By integrating clinical risk factors and metrics from tri-IVIM, a predictive nomogram exhibited the highest diagnostic accuracy, potentially aiding in the noninvasive and preoperative assessment of MVI.Keywords: tri-exponential intra-voxel incoherent motion, diffusion weighted imaging, hepatocellular carcinoma, microvascular invasion

Saiyue Deng,1 Quan Wang,2 Jingjing Fan,3 Xiaoyun Yang,3 Junhua Mei,4 Jiajia Lu,5 Guohua Chen,4 Yuan Yang,1 Wenhua Liu,6 Runsen Wang,7 Yujia Han,7 Rong Sheng,7 Wei Wang,1 Li Ba,1 Fengfei Ding1,8 1Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China; 2School of Nursing, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000, People’s Republic of China; 3Cardiac Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China; 4Department of Neurology, Wuhan No.1 Hospital, Wuhan, 430022, People’s Republic of China; 5Cardiac Unit, Wuhan No.1 Hospital, Wuhan, 430022, People’s Republic of China; 6Department of Clinical Research Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000, People’s Republic of China; 7Huawei Technologies Co, Shenzhen, People’s Republic of China; 8Department of Pharmacology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of ChinaCorrespondence: Fengfei Ding, Department of Pharmacology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of China, Tel +86 134 7625 5813, Email fengfei_ding@fudan.edu.cn Li Ba, Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China, Tel +86 136 0764 1809, Email bali2015@126.comPurpose: Heart rate variability (HRV) indices have been used as stress indicators. Rare studies investigated the associations of circadian rhythms of the HRV indices with the stress, mood, and sleep conditions in populations under stress.Methods: In total 257 female participants (203 shift workers and 54 non-shift workers) were included. All the participants completed a structured questionnaire to assess the stress, mood, and sleep conditions and performed 24-hour Holter electrocardiogram monitoring on the day away from shifts. Using epochs of 1-min or 5-min beat-to-beat intervals, the HRV indices (SDNN, RMSSD, LF, HF, LF/HF, and LFnu, SD1, SD2, SD1/SD2) were plotted as a function of time and fitted into cosine periodic curves, respectively. Three mathematical parameters based on the cosine periodic curves were extracted, MESOR (M, overall averages of the cosine curve), amplitude (A, amplitude of the peak of the cosine curve), and acrophase (θ, latency to the peak) to quantify the circadian rhythms of the HRV indices. Multivariable linear regression models were used to reveal the associations of these parameters with the clinical assessments of stress, mood, or sleep conditions, as well as with the 24-h averages of the HRV indices.Results: The parameters M and A of SDNN, RMSSD, LF, and HF, and θ of LF/HF and LFnu significantly differ between shift and non-shift workers. The parameter θ of LF/HF positively correlates with the severity of stress and anxiety. The parameter A of LF/HF and LFnu also positively correlates with daytime sleepiness and sleep fragmentation. In addition, the parameters M and A instead of θ of SDNN, RMSSD, LF, LF/HF, and LFnu significantly correlate with the 24-h averages of HRV indices.Conclusion: The circadian rhythms of the HRV indices over 24 hours can, to some extent, predict the severity of stress, emotion and sleep conditions in female populations under stress.Keywords: circadian rhythms, HRV indices, mental health, stress, sleepiness, fatigue, sleep fragmentation

N6-methyladenosine (m6A) modification, a eukaryotic messenger RNA modification catalyzed by methyltransferase-like 3 (METTL3), plays a pivotal role in stem cell fate determination. Calvarial bone development and maintenance are orchestrated by the cranial sutures. Cathepsin K (CTSK)–positive calvarial stem cells (CSCs) contribute to mice calvarial ossification. However, the role of m6A modification in regulating Ctsk+ lineage cells during calvarial development remains elusive. Here, we showed that METTL3 was colocalized with cranial nonosteoclastic Ctsk+ lineage cells, which were also associated with GLI1 expression. During neonatal development, depletion of Mettl3 in the Ctsk+ lineage cells delayed suture formation and decreased mineralization. During adulthood maintenance, loss of Mettl3 in the Ctsk+ lineage cells impaired calvarial bone formation, which was featured by the increased bone porosity, enhanced bone marrow cavity, and decreased number of osteocytes with the less-developed cellular outline. The analysis of methylated RNA immunoprecipitation sequencing and RNA sequencing data indicated that loss of METTL3 reduced Hedgehog (Hh) signaling pathway. Restoration of Hh signaling pathway by crossing Sufufl/+ alleles or by local administration of SAG21 partially rescued the abnormity. Our data indicate that METTL3 modulates Ctsk+ lineage cells supporting calvarial bone formation by regulating the Hh signaling pathway, providing new insights for clinical treatment of skull vault osseous diseases. [ABSTRACT FROM AUTHOR]

Abstract Three‐coil inductive power transfer (IPT) charging system can not only achieve inherent constant current (CC) to constant voltage (CV) transition but also tolerate load open‐circuit. However, due to the cross‐coupling between the auxiliary coil and the receiver coil, the output voltage in CV mode may deviate from the CV voltage significantly, which makes the design freedom of the three‐coil coupler low. By replacing the auxiliary coil with a transformer, an improved auxiliary circuit is proposed in this paper to address the cross‐coupling issue and to increase the design freedom of the loosely coupled transformer (LCT). The improved auxiliary circuit can achieve load short‐circuit and open‐circuit protection. Besides, the optimization design of LCT is easy to achieve by load impedance matching. The operating principle and parameters design of the improved auxiliary circuit are discussed. A 1 kW experimental prototype is built to verify the feasibility of the proposed method.

The oral gingival barrier is a constantly stimulated and dynamic environment where homeostasis is often disrupted, resulting in inflammatory periodontal diseases. Type 2 diabetes (T2D) has been reported to be associated with gingival barrier dysfunction, but the effect and underlying mechanism are inconclusive. Herein, we performed single-cell RNA sequencing (scRNA-seq) of gingiva from leptin receptor-deficient mice (db/db) to examine the gingival heterogeneity in the context of T2D. Periodontal health of control mice is characterized by populations of Krt14+-expressing epithelial cells and Col1a1+-fibroblasts mediating immune homeostasis primarily through the enrichment of innate lymphoid cells. The db/db gingiva exhibited decreased epithelial/stromal ratio and dysfunctional barrier. We further observed stromal, particularly fibroblast immune hyperresponsiveness, linked to the recruitment of myeloid-derived cells at the db/db gingiva. Both scRNA-seq and histological analysis suggested the inflammatory signaling between fibroblasts and neutrophils as a potential driver of diabetes-induced periodontal damage. Notably, the "immune-like" stromal cells were wired toward the induction of gingival IL-17A hyperresponsiveness in db/db mice. Our work reveals that the "immune-like" fibroblasts with transcriptional diversity are involved in the innate immune homeostasis at the diabetic gingiva. It highlights a potentially significant role of these cell types in its pathogenesis. [ABSTRACT FROM AUTHOR]

Deep learning has advanced object detection, but generalizing models from source to target domains remains a challenge due to multi-level domain drift and untransferable information. To address this, we propose a transferability-aware hierarchical domain-consistent object detector (THNet), incorporating instance-level, pixel-level, and image-level alignment subnets for robust cross-domain detection. THNet first aligns local foreground-transferable features through pixel-level adversarial learning and foreground-aware attention, then captures global domain-invariant features via image-level subnet with channel-transferable attention. Additionally, a prototype graph convolutional network alleviates instance distribution differences by maximizing inter-class distances and minimizing intra-class distances. A domain-consistent loss harmonizes training for better convergence in multi-level domain alignment. Extensive experiments demonstrate that THNet outperforms state-of-the-art methods on multiple cross-domain datasets, achieving top accuracies of 51.9%, 46.0%, 41.2%, and 51.9% across different tasks.

The single image super-resolution based on deep learning has achieved extraordinary performance. However, due to inevitable environmental or technological limitations, some images not only have low resolution but also low brightness. The existing super-resolution methods for restoring images through low-light input may encounter issues such as low brightness and many missing details. In this paper, we propose a semantic-aware guided low-light image super-resolution method. Initially, we present a semantic perception guided super-resolution framework that utilizes the rich semantic prior knowledge of the semantic network module. Through the semantic-aware guidance module, reference semantic features and target image features are fused in a quantitative attention manner, guiding low-light image features to maintain semantic consistency during the reconstruction process. Second, we design a self-calibrated light adjustment module to constrain the convergence consistency of each illumination estimation block by self-calibrated block, improving the stability and robustness of output brightness enhancement features. Third, we design a lightweight super resolution module based on spatial and channel reconstruction convolution, which uses the attention module to further enhances the super-resolution reconstruction capability. Our proposed model surpasses methods such as RDN, RCAN, and NLSN in both qualitative and quantitative analysis of low-light image super-resolution reconstruction. The experiment proves the efficiency and effectiveness of our method.

Abstract MAVS is an adapter protein involved in RIG-I-like receptor (RLR) signaling in mitochondria, peroxisomes, and mitochondria-associated ER membranes (MAMs). However, the role of MAVS in glucose metabolism and RLR signaling cross-regulation and how these signaling pathways are coordinated among these organelles have not been defined. This study reports that RLR action drives a switch from glycolysis to the pentose phosphate pathway (PPP) and the hexosamine biosynthesis pathway (HBP) through MAVS. We show that peroxisomal MAVS is responsible for glucose flux shift into PPP and type III interferon (IFN) expression, whereas MAMs-located MAVS is responsible for glucose flux shift into HBP and type I IFN expression. Mechanistically, peroxisomal MAVS interacts with G6PD and the MAVS signalosome forms at peroxisomes by recruiting TNF receptor-associated factor 6 (TRAF6) and interferon regulatory factor 1 (IRF1). By contrast, MAMs-located MAVS interact with glutamine-fructose-6-phosphate transaminase, and the MAVS signalosome forms at MAMs by recruiting TRAF6 and TRAF2. Our findings suggest that MAVS mediates the interaction of RLR signaling and glucose metabolism.

In nature, rock masses often exhibit fissures, and varying external forces lead to different rates of loading on fissured rock masses. By studying the influence of the loading rate on the mechanical properties of fractured rock mass and AE characteristic parameters, it can provide a theoretical basis for the safety and stability prediction of engineering rock mass. To investigate the influence of loading rates on fissured rock masses, this study utilizes surrogate rock specimens resembling actual rock bodies and prefabricates two fissures. By conducting uniaxial compression acoustic emission tests at different loading rates, the study explores changes in their mechanical properties and acoustic emission characteristic parameters. Research findings indicate the following: (1) Prefabricated fissures adversely affect the stability of specimens, resulting in lower strength compared to intact specimens. Under the same fissure inclination angle, peak strength, elastic modulus, and loading rate exhibit a positive correlation. When the fissure inclination angle varies from 0° to 60° under the same loading rate, the peak strength of specimens generally follows a “V”-shaped trend, decreasing initially and then increasing, with the minimum peak strength observed at α = 30°. (2) Prefabricated fissure specimens primarily develop tensile cracks during loading, gradually transitioning to shear cracks, ultimately leading to shear failure. (3) The variation patterns of AE (acoustic emission) characteristic parameters under the influence of loading rate differ: AE event count, AE energy, and cumulative AE energy show a positive correlation with loading rate, while cumulative AE event count gradually decreases with increasing loading rate. (4) AE characteristic parameters exhibit good correlation with the stress–strain curve and can be divided into four stages. The changes in AE characteristic parameters correspond to the changes in the stress–strain curve. With increasing loading rate, AE signals in the first three stages gradually stabilize, focusing more on the fourth stage, namely the post-peak stage, where the specimens typically experience maximum AE signals accompanying final failure.

Although the effect of campus landscape space on stress relief among college students has been confirmed, few existing studies have considered the impact on stress recovery from the perspective of factor combination, and the key visual elements and the most effective combination of visual elements to relieve stress are still unclear. This study attempts to conduct a natural experiment within Chinese campuses, measuring physiological indicators of stress such as heart rate (HR), frequency domain index of heart rate variability (LF/HF), skin conductance level (SCL), skin temperature (SKT), and respiratory rate (RESP) using physiological instruments. It explored the effects of visual elements and their combinations in campus landscape spaces on short-term stress relief among college students through semantic segmentation, multifactorial analysis of variance, and post hoc multiple comparison methods. Research results demonstrate that the presence of water elements in the field of vision can effectively improve the stress relief effects of landscape spaces. Reasonable combinations of natural landscape elements and artificial landscape elements in the design can also effectively promote stress relief among students. Building facade area and sky area, water area and sky area, and plant species and pavement area are three combinations of factors with the strongest interactive effects. “Natural water scenery” and “exquisite artificial” are two campus landscape design patterns most conducive to short-term stress relief.

Kondo systems offer a rich platform to study the interplay between strong correlations and topology. Here the authors observe a large anomalous Hall conductivity in a Kondo ferromagnet USbTe, which they attribute to the Berry curvature originating from flat bands induced by the Kondo hybridization.

With the increasing amount of real data, the challenges of large-scale model operations as well as poor generalization capacity, making selection of an appropriate feature set a significant concern. This study proposes ImprovedRFECV, an enhanced approach for cross-validated recursive feature elimination (RFECV). The algorithm first enhances the robustness of the optimal feature subset through random sampling of different data, building multiple models, and comparing their scores. Simultaneously, the L1 and L2 regularization terms are introduced to evaluate the value of each feature more comprehensively, thus reducing the impact on the anti-interference term and further improving the accuracy of the algorithm and its stability. Furthermore, a multi-model ensemble learning framework is employed to enhance generalization ability and effectively prevent overfitting. Lastly, a both-end expansion removal strategy is adopted to address the issue of strong covariance among features while enhancing the algorithm’s flexibility. The experimental results demonstrate that, compared to the RFECV algorithm, the ImprovedRFECV algorithm achieves fewer optimal average features and outperforms the optimal feature subset across five datasets spanning five different domains, demonstrating the algorithm’s high level of robustness and generalization ability.

Stem cells play a critical role in bone regeneration. Multiple populations of skeletal stem cells have been identified in long bone, while their identity and functions in alveolar bone remain unclear. Here, we identified a quiescent leptin receptor-expressing (LepR+) cell population that contributed to intramembranous bone formation. Interestingly, these LepR+ cells became activated in response to tooth extraction and generated the majority of the newly formed bone in extraction sockets. In addition, genetic ablation of LepR+ cells attenuated extraction socket healing. The parabiosis experiments revealed that the LepR+ cells in the healing sockets were derived from resident tissue rather than peripheral blood circulation. Further studies on the mechanism suggested that these LepR+ cells were responsive to parathyroid hormone/parathyroid hormone 1 receptor (PTH/PTH1R) signaling. Collectively, we demonstrate that LepR+ cells, a postnatal skeletal stem cell population, are essential for alveolar bone regeneration of extraction sockets. [ABSTRACT FROM AUTHOR]

Gear noise has become an important index to check the gear processing quality， and it is also a common problem in gear application. In order to effectively solve the noise problem of gears in use， a method which can appropriately increase the helix angle of helical gears to reduce the gear meshing noise is adopted. Taking the first stage motor shaft and helical gears of the door controlled reducer as the analysis object， the model is established and simplified by three-dimensional software， and the sound pressure level of 19°~23° helical angle gear meshing is simulated using the acoustic module in Comsol Multiphysics software； the meshing sound pressure levels of 19°~23° helical angle gears under no-load and loaded conditions are measured with UT353 decibel instrument from close to and 1 m away. The test results show that by improving the helix angle， the reducer noise is optimized by 2~6 dB， and the optimization effect under loaded conditions is better than that under no-load condition. Finally， the stability of mass production of motor shafts and gears is ensured by limiting the use times of cutting tools.

Abstract The role of nematic fluctuations for unconventional superconductivity has been the subject of intense discussions for many years. In iron-based superconductors, the most established probe for electronic-nematic fluctuations, i.e. the elastoresistivity seems to imply that superconductivity is reinforced by electronic-nematic fluctuations, since the elastoresistivity amplitude peaks at or close to optimal T c . However, on the over-doped side of the superconducting dome, the diminishing elastoresistivity suggests a negligible importance in the mechanism of superconductivity. Here we introduce the Nernst coefficient as a genuine probe for electronic nematic fluctuations, and we show that the amplitude of the Nernst coefficient tracks the superconducting dome of two prototype families of iron-based superconductors, namely Rh-doped BaFe2As2 and Co-doped LaFeAsO. Our data thus provide fresh evidence that in these systems, nematic fluctuations foster the superconductivity throughout the phase diagram.

BackgroundObesity in pediatric patients is strongly associated with increased vascular and metabolic risk. Prediabetes is present in up to 1 in 5 adolescents, aged 12-18 years-old, though is thought to remit spontaneously in a significant portion. Pediatric patients with type 2 diabetes mellitus (T2D) have a more rapid decline of beta-cell function and progression to treatment failure than adult T2D patients. Thus, there is a strong interest in better understanding the natural history of prediabetes in these youth. We aimed to evaluate the real-world rate of progression of prediabetes to T2D in adolescent patients.MethodsThis is a retrospective study of 9,275 adolescent subjects aged 12-21 years-old with at least 3 years of de-identified commercial claims data and a new diagnosis of prediabetes during the observation period. Enrollees with a T2D diagnosis and/or diabetes medication use in the 1 year prior to prediabetes diagnosis or a T2D diagnosis in the 1 month following prediabetes diagnosis were excluded. Enrollees with diagnoses of type 1 diabetes (T1D) or polycystic ovarian syndrome over the 3 years were also excluded. Progression to T2D was defined by claims data of two T2D diagnoses at least 7 days apart, HbA1c ≥ 6.5%, and/or prescription of insulin without known T1D. Enrollees were followed for 2 years after prediabetes diagnosis.ResultsOverall, 232 subjects (2.5%) progressed from prediabetes to T2D. There were no differences found in T2D progression based on sex or age. Progression to T2D occurred at a median of 302 days after prediabetes diagnosis (IQR 123 to 518 days). This study was limited by the lack of laboratory/anthropometric data in administrative claims, as well as the exclusion of 23,825 enrollees for lack of continuous commercial claims data over 3 years.ConclusionIn the largest sample to date on adolescent prediabetes, we found a 2.5% progression of prediabetes to T2D over a median duration of about one year.

Abstract The temperature dependence of the low-energy magnetic excitations in the spin-triplet superconductor UTe2 was measured via inelastic neutron scattering in the normal and superconducting states. These excitations have a peak instensity at 4 meV, follow the Brillouin zone edges near the crystallographic b-axis, obey the paramagnetic structural symmetry, and track the temperature evolution of the heavy fermion bulk magnetic susceptibility. Thus, the imaginary part of the dynamic susceptibility follows the behavior of interband correlations in a hybridized Kondo lattice with an appropriate characteristic energy. These excitations are a lower-dimensional analog of phenomena observed in other Kondo lattice materials, such that their presence is not necessarily due to dominance of ferromagnetic or antiferromagnetic correlations. The onset of superconductivity alters the magnetic excitations noticeably on the same energy scales, suggesting that these changes originate from additional electronic structure modification.

Abstract Malignant phyllodes tumors (PT) are rare aggressive fibroepithelial neoplasms with high metastatic potential and lack effective therapy. We established a patient-derived xenograft (PDX) and cell line model (designated MPT-S1) of malignant PT which demonstrated clinical response to pazopanib. Whole exome sequencing identified somatic mutations in TP53, RB1, MED12, and KMT2D. Immunohistochemistry and genomic profiles of the tumor, PDX and cell line were concordant. In keeping with clinical observation, pazopanib reduced cell viability in a dose-dependent manner and evoked apoptosis, and led to significant abrogation of in vivo tumor growth. Whole transcriptomic analysis revealed that pazopanib decreased expression of genes involved in oncogenic and apoptosis signaling. We also observed decreased expression of ENPP1, with known roles in cancer invasion and metastasis, as well as STING pathway upregulation. Accordingly, pazopanib induced micronuclei formation, and evoked phospho-TBK1 and PD-L1 expression. In an additional cohort of malignant PT (n = 14), six (42.9%) showed comparable or higher levels of ENPP1 relative to MPT-S1, highlighting its potential role as a therapeutic target. In conclusion, we established MPT-S1, a new PDX and cell line model, and provided evidence for the clinical efficacy of pazopanib in malignant PT.

Abstract Magnetic field-induced superconductivity is a fascinating quantum phenomenon, whose origin is yet to be fully understood. The recently discovered spin-triplet superconductor, UTe2, exhibits two such superconducting phases, with the second one reentering in the magnetic field of 45 T and persisting up to 65 T. More surprisingly, in order to induce this superconducting phase, the magnetic field has to be applied in a special angle range, not along any high symmetry crystalline direction. Here we investigated the evolution of this high-field-induced superconducting phase under pressure. Two superconducting phases merge together under pressure, and the zero resistance persists up to 45 T, the field limit of the current study. We also reveal that the high-field-induced superconducting phase is completely decoupled from the first-order field-polarized phase transition, different from the previously known example of field-induced superconductivity in URhGe, indicating superconductivity boosted by a different paring mechanism.

Current methods for acquiring dissemination kinetics of rare circulating tumor cells (CTCs) that form metastases have several limitations. Here, the authors show an approach for measuring endogenous CTC kinetics by continuously exchanging CTC-containing blood between un-anesthetized, tumor-bearing mice and healthy, tumor-free counterparts.

Chiral superconductors are predicted to realize Majorana normal fluid at its boundary, but remain elusive experimentally. Here, Bae et al. report anomalous surface normal fluid response in UTe2 single crystal which is further attributed to a chiral spin-triplet pairing state.

Medical video is important for medical diagnosis. However, due to the influence of the network bandwidth and hardware equipment, some medical videos have low resolution, which is not conducive for diagnosing early diseases with small lesions. Medical videos with super-resolutions can help doctors clearly observe small lesions and increase the likelihood of diagnosing and curing diseases. In this paper, we propose an advanced medical video super-resolution method based on an asymmetric back-projection network. We construct a single-frame medical video super-resolution model as the benchmark model, combine the optical flow algorithm and multiframe fusion strategy to propose a medical video super-resolution method based on an asymmetric back-projection network with multilevel error feedback, and train high-quality and high-speed medical video super-resolution models. Finally, we use the proposed method to create super-resolution versions of different types of low-resolution medical videos and evaluate the quality and efficiency of reconstruction. The experimental results show that the proposed medical video super-resolution method achieves superior performance compared to that of other methods considered in this work.

A graphical analysis model is proposed to explore the possible structural patterns and efficiency. The research shows that the existence of cycle power is determined by the structure itself and has nothing to do with the characteristic parameter P. Six structural types with wide transmission ratios were proposed. In combination with the analysis model， the relationship between the transmission ratio and efficiency is discussed， and the transmission ratio range that there must be a cycle power in the condition of characteristic parameter P in [3，8] is obtained. Finally， the efficiency of a scheme is analyzed with this method， and the efficiency is improved by changing the tooth ratio.

Human-driven Edge Computing (HEC) integrates the elements of humans, devices, Internet and information, and mobile crowd sensing become an important means of data collection. In HEC, the data collected from large-scale sensing usually includes a variety of modalities. These different modality data contain unique information and attributes, which can be complementary. Combining data from many different modalities will get more information. However, current deep learning is usually only for bimodal data. In order for artificial intelligence to make further breakthroughs in understanding our real world, it needs to be able to process data in different modalities together. The key step is to be able to map these different modalities data into the same space. In order to process multimodal data better, we propose a fusion and classification method for multimodal data. First, a multimodal data space is constructed, and data of different modalities are mapped into the multimodal data space to obtain a unified representation of different modalities data. Then, through bilinear pooling, the representations of different modality are fused, and the fused vectors are used in the classification task. Through the experimental verification on the multi-modal data set, it proves that the multi-modal fusion representation is effective, and the classification effect is more accurate than the single-modal data.

The seepage characteristics of rocks under conditions of multi-field activity have always been important in the field of rock mechanics. This study used the MTS815 multi-functional electro-hydraulic servo rock testing machine to conduct seepage tests on long-flame coal specimens under different confining pressures, water pressures, and temperatures. This paper presents and discusses the seepage characteristics of coal specimens under the action of thermal hydraulic mechanical multi-field combinations. Considering parameters such as volumetric strain, temperature, thermal expansion coefficient, and initial porosity, the relationships of each parameter with porosity were obtained. The test results revealed that the volumetric strain of coal specimens increased gradually with the increase of temperature. The dynamic viscosity of water decreased with the increase of temperature, which accelerated the movement and circulation of water molecules. The increase in temperature caused the volume of the coal specimen to expand, the pores in the coal specimen squeezed against each other, the pore volume decreased, and the size of the seepage channel slowly decreased, which inhibited the seepage process. Furthermore, permeability gradually decreased with the increase of temperature. This inhibited the occurrence of seepage, and the higher the confining pressure, the lower was the permeability. The porosity of coal specimens decreased with the increase in temperature, which had an inhibitory effect on the seepage behavior. The results of this study provide experimental and theoretical support for the safe mining of coal and rock in underground mines.

Background Despite its clinical significance, the risk of severe infection requiring hospitalization among outpatients with severe acute respiratory syndrome coronavirus 2 infection who receive angiotensin‐converting enzyme (ACE) inhibitors and angiotensin receptor blockers (ARBs) remains uncertain. Methods and Results In a propensity score–matched outpatient cohort (January–May 2020) of 2263 Medicare Advantage and commercially insured individuals with hypertension and a positive outpatient SARS‐CoV‐2, we determined the association of ACE inhibitors and ARBs with COVID‐19 hospitalization. In a concurrent inpatient cohort of 7933 hospitalized with COVID‐19, we tested their association with in‐hospital mortality. The robustness of the observations was assessed in a contemporary cohort (May–August). In the outpatient study, neither ACE inhibitors (hazard ratio [HR], 0.77; 0.53–1.13, P=0.18) nor ARBs (HR, 0.88; 0.61–1.26, P=0.48) were associated with hospitalization risk. ACE inhibitors were associated with lower hospitalization risk in the older Medicare group (HR, 0.61; 0.41–0.93, P=0.02), but not the younger commercially insured group (HR, 2.14; 0.82–5.60, P=0.12; P‐interaction 0.09). Neither ACE inhibitors nor ARBs were associated with lower hospitalization risk in either population in the validation cohort. In the primary inpatient study cohort, neither ACE inhibitors (HR, 0.97; 0.81–1.16; P=0.74) nor ARBs (HR, 1.15; 0.95–1.38, P=0.15) were associated with in‐hospital mortality. These observations were consistent in the validation cohort. Conclusions ACE inhibitors and ARBs were not associated with COVID‐19 hospitalization or mortality. Despite early evidence for a potential association between ACE inhibitors and severe COVID‐19 prevention in older individuals, the inconsistency of this observation in recent data argues against a role for prophylaxis.

Abstract With the development of wireless communications and networks, HCC (human-centred computing) has attracted considerable attention in recent years throughout the medical field. HCC can provide an effective integration of various medical auxiliary diagnosis models using machine learning algorithms. In medical HCC, deep learning has demonstrated its powerful ability in the field of computer vision. However, image processing based on deep learning usually requires a large amount of labeled data, which requires significant resources since it needs to be completed by doctors, and it is difficult to collect a large amount of data for some rare diseases. Therefore, how to use the deep learning method to obtain an effective auxiliary diagnosis model based on a small sample or zero sample data set has become an important issue in the study of medical auxiliary diagnosis. We proposes an auxiliary diagnosis model acquisition method based on a variational auto-encoder and zero sample augmentation technology, and the incremental update training program based on wireless communications and networks is designed to obtain the auxiliary diagnosis model to solve the difficulty of collecting a large amount of valid data. The experimental results show that the model obtained by the above method based on a small sample or zero sample data set can effectively diagnose the types of skin diseases, which helps doctors make better judgments.

Electrons in uranium-based materials are often on the border between localised and itinerant behaviour, which can lead to unusual magnetic behaviour. Here the authors combine experiment and theory to show that USb2 may be an unusually high temperature example of a singlet-ground-state magnet.

A multiphoton absorption is one of the main nonlinear optical characteristics of semiconductor quantum dots (QDs). In this paper, we report on four-photon absorption of ZnSe:Mn QDs. The four-photon excitation spectrum is characterized under 1350 nm excitation with 50 fs femtosecond laser pulses. The experimental results indicate that the highest absorption coefficient was 2.87 × 10-5 cm5 /GW3 for Mn doping of 170 μl, and corresponding cross-section is 2.03 × 10-79 cm8·s3. We also proved that it has low biotoxicity. The results of our studies suggest that these QDs can potentially be used to detect electric fields, limit laser power, and for biosensing applications.

Purpose: To compare the incidence of contrast medium-induced acute kidney injury (AKI) after intravenous (IV) administration of iodixanol for computed tomographic (CT) angiography versus intraarterial (IA) injection of iodixanol or low osmolar contrast medium (LOCM) for digital subtraction angiography (DSA) within the same population suspected of peripheral arterial occlusive disease (PAOD). Materials and Methods: CT angiography was performed with IV iodixanol 320 mgI/mL. After a washout period of 3-14 days, DSA was performed with IA iodixanol or LOCM. Serum creatinine was measured at baseline and 24 hours after administration. Contrast medium-induced AKI was defined by a serum creatinine increase of at least 25% versus baseline at 24 hours. Data were analyzed with χ(2) statistics. Results: Mean baseline serum creatinine values were comparable between CT angiography with IV contrast medium and DSA with IA contrast medium (93.3 μmol/L ± 52.92 vs 92.8 μmol/L ± 61.70). The incidence of AKI for CT angiography after IV iodixanol administration was 7.6% (20 of 264), which was not statistically different than the 8.7% incidence (22 of 253) for DSA with IA iodixanol or LOCM (P = .641). In the 143 patients who received only iodixanol for both procedures, incidences of contrast medium-induced AKI were comparable after IV (7.0%) and IA (5.6%) administration (P = .626). Conclusions: The rates of contrast medium-induced AKI are not statistically different between IV iodixanol for CT angiography and IA iodixanol or another LOCM for DSA in the same population with suspected PAOD. [ABSTRACT FROM AUTHOR]

Two novel 2D and 3D bimetallic CdNi coordination polymers, Cd(2Mpz)(HO)Ni(CN) (I) (2Mpz: 2-methylpyrazine) and Cd(2Epz)(HO)Ni(CN) (II) (2Epz: 2-ethylpyrazine), have been synthesized and characterized by elemental analysis, powder X-ray diffraction, IR spectra, fluorescent spectra, single crystal X-ray diffraction and thermogravimetric analysis. Based on the analysis of structures, it can be found that the Cd(II) ions in the two complexes have the similar octahedral coordination geometry of CdNO, which are linked by [Ni(CN)] units at the equatorial plane to form 2D sheet layers [CdNi(CN)]. However, it's noted that the coordination environment of Ni(II) ions and action of ligands are different. All the Ni(II) ions in I are the five-coordinated pentahedron configuration and 2-methylpyrazine acts as a bridging ligand linking the Cd(II) and Ni(II) ions of the adjacent layers, leading to the 3D metal-organic framework. The structure of II indicates all the Ni(II) ions are the four-coordinated square plane and 2-ethylpyrazine is a terminal ligand coordinated to Cd(II) ions, forming the 2D layer structure. Moreover, the two complexes display significant thermal stability and fluorescent properties. [ABSTRACT FROM AUTHOR]

With the development of the new detection methods and the function of fluorescent molecule, researchers hope to further explore the internal mechanisms of organisms, monitor changes in the intracellular microenvironment, and dynamic processes of molecular interactions in cells. Fluorescence resonance energy transfer (FRET) describes the energy transfer process between donor fluorescent molecules and acceptor fluorescent molecules. It is an important means to detect protein–protein interactions and protein conformation changes in cells. Fluorescence lifetime imaging microscopy (FLIM) enables noninvasive measurement of the fluorescence lifetime of fluorescent particles in vivo. The FRET–FLIM technology, which is use FLIM to quantify and analyze FRET, enables real-time monitoring of dynamic changes of proteins in biological cells and analysis of protein interaction mechanisms. The distance between donor and acceptor and their respective fluorescent lifetime, which are of great importance for studying the mechanism of intracellular activity can be obtained by data analysis and algorithm fitting.

Customer requirement preference is an important part of customer satisfaction. In view of similar case retrieval technology for existing product level, in the process of solving similar cases, there is no consideration for customer requirement preference. This article proposes a similar case solution method considering customer requirement preference. First, we deal with the expression of customer requirements and transform them into operable parameter forms according to the mapping model. Second, the preference graph is used to analyze the customer’s requirement preference, to determine the preference weight, and to weigh the final weight of the requirement node with the initial weight determined by the fuzzy analytic hierarchy process. Finally, the similarity degree solving model of requirement node and product case attribute parameters is established. By integrating the weights of the above-mentioned nodes, the similarity of the product case is obtained, and a more satisfied case of the customer is obtained. Taking the automated guided vehicle car product as an example, the effectiveness of the proposed method is verified.

This work demonstrates the principle of a novel cancer therapeutic method using magnetic fluids to block the blood supply to a tumor in order to starve it. Plastic tubes are used to simulate the simplest blood network. The sealing effect to the fluid flow is easily achieved at low particle concentrations with strong pressure resistance and reasonable sealing times at low flow rate (Q = 0.078 ml/min). At high flow rate (Q > 0.62 ml/min), oscillations in pressure and step increases in weight of the fluid are found. [ABSTRACT FROM PUBLISHER]

Lower plasma levels of high-density lipoproteins (HDL) in adolescents with type 2 diabetes (T2D) have been associated with a higher pulse wave velocity (PWV), a marker of arterial stiffness. Evidence suggests that HDL proteins or particle subspecies are altered in T2D and these may drive these relationships. In this work, we set out to reveal any specific proteins and subspecies that are related to arterial stiffness in youth with T2D from proteomics data. Plasma and PWV measurements were previously acquired from lean and T2D adolescents. Each plasma sample was separated into 18 fractions and evaluated by mass spectrometry. Then, we applied a validated network-based computational approach to reveal HDL subspecies associated with PWV. Among 68 detected phospholipid-associated proteins, we found that seven were negatively correlated with PWV, indicating that they may be atheroprotective. Conversely, nine proteins show positive correlation with PWV, suggesting that they may be related to arterial stiffness. Intriguingly, our results demonstrate that apoA-I and histidine-rich glycoprotein may reverse their protective roles and become antagonistic in the setting of T2D. Furthermore, we revealed two arterial stiffness-associated HDL subspecies, each of which contains multiple PWV-related proteins. Correlation and disease association analyses suggest that these HDL subspecies might link T2D to its cardiovascular-related complications.

In this paper, we investigated the problem of computer-aided diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) using machine learning techniques. With the ADHD-200 dataset, we developed a Support Vector Machine (SVM) model to classify ADHD patients from typically developing controls (TDCs), using the regional brain volumes as predictors. Conventionally, the volume of a brain region was considered to be an anatomical feature and quantified using structural magnetic resonance images. One major contribution of the present study was that we had initially proposed to measure the regional brain volumes using fMRI images. Brain volumes measured from fMRI images were denoted as functional volumes, which quantified the volumes of brain regions that were actually functioning during fMRI imaging. We compared the predictive power of functional volumes with that of regional brain volumes measured from anatomical images, which were denoted as anatomical volumes. The former demonstrated higher discriminative power than the latter for the classification of ADHD patients vs. TDCs. Combined with our two-step feature selection approach which integrated prior knowledge with the recursive feature elimination (RFE) algorithm, our SVM classification model combining functional volumes and demographic characteristics achieved a balanced accuracy of 67.7%, which was 16.1% higher than that of a relevant model published previously in the work of Sato et al. Furthermore, our classifier highlighted 10 brain regions that were most discriminative in distinguishing between ADHD patients and TDCs. These 10 regions were mainly located in occipital lobe, cerebellum posterior lobe, parietal lobe, frontal lobe, and temporal lobe. Our present study using functional images will likely provide new perspectives about the brain regions affected by ADHD.

Highly yield Cu2SnS3 nanocrystals (CTS NCs) have been attracted more attentions in these years, the CTS NCs with strong absorption in near-infrared (NIR) region which can serve as the contrast agent of Optical Coherence Tomography (OCT) imaging. These NCs can be synthesized by facile method, and exhibit a Localized Surface Plasmon Resonance (LSPR) peak in NIR region. The LSPR peak position of the CTS NCs depends on the ratio of copper to tin in the synthesis process. The highest intensity of LSPR at 1380nm when Cu:Sn ratio reach to 9:1. The TEM analysis and X-ray diffraction pattern reveals the formation of CTS NCs with an average size of 6nm and the structure is kesterite crystal phase. In order to apply the NCs in vivo and in vitro study, we used PEGylated phospholipid (DSPE-PEG) to modified NCs, and the colloidal stability and cell viability of DSPE-PEG CTS NCs are very suitable for the in vivo OCT imaging study. To quantitatively analyze the contrast effect of DSPE-PEG CTS NCs, the contrast agent was injected from the tail vein of ICR mice, then applied the SD-OCT system monitor the vein of the mouse pinna for 30 minutes. The results indicated that the DSPE-PEG CTS NCs created an obvious signal in the OCT imaging process, which provide the basis for the application of CTS NCs as the contrast agent for the bioimaging study.

Fibronectin (FN) is a high molecular weight extracellular matrix protein that functions in cell adhesion, growth, migration, and embryonic development. However, little is known about the role of FN during viral infection. In the present study, we found significantly higher levels of FN in sera, and liver tissues from hepatitis B virus (HBV) patients relative to healthy individuals. HBV expression enhanced FN mRNA and protein levels in the hepatic cell lines Huh7 and HepG2. HBV infection of susceptible HepG2-sodium taurocholate co-transporting polypeptide cells also increased FN expression. We also found that transcriptional factor specificity protein 1 was involved in the induction of FN by HBV. Knockdown of FN expression significantly inhibited HBV DNA replication and protein synthesis through activating endogenous IFN-α production. In addition, FN interacted with the transforming growth factor β-activated protein kinase 1 (TAK1) and TAK1-binding protein complex and attenuated interferon signaling by inhibiting TAK1 phosphorylation. Furthermore, the nuclear translocation of NF-κB/p65 was found to be inhibited by FN. We also observed that FN promoted HBV enhancers to support HBV expression. These results suggest novel functions of endogenous FN involved in immune evasion and maintenance of HBV replication.