Pedicled iliac crest bone flap transfer for the treatment of upper femoral shaft fracture nonunion: An anatomic study and clinical applications

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146632/1/micr30278.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146632/2/micr30278_am.pd

Fourier-Flow model generating Feynman paths

As an alternative but unified and more fundamental description for quantum physics, Feynman path integrals generalize the classical action principle to a probabilistic perspective, under which the physical observables' estimation translates into a weighted sum over all possible paths. The underlying difficulty is to tackle the whole path manifold from finite samples that can effectively represent the Feynman propagator dictated probability distribution. Modern generative models in machine learning can handle learning and representing probability distribution with high computational efficiency. In this study, we propose a Fourier-flow generative model to simulate the Feynman propagator and generate paths for quantum systems. As demonstration, we validate the path generator on the harmonic and anharmonic oscillators. The latter is a double-well system without analytic solutions. To preserve the periodic condition for the system, the Fourier transformation is introduced into the flow model to approach a Matsubara representation. With this novel development, the ground-state wave function and low-lying energy levels are estimated accurately. Our method offers a new avenue to investigate quantum systems with machine learning assisted Feynman Path integral solving

Progressive Learning with Visual Prompt Tuning for Variable-Rate Image Compression

In this paper, we propose a progressive learning paradigm for transformer-based variable-rate image compression. Our approach covers a wide range of compression rates with the assistance of the Layer-adaptive Prompt Module (LPM). Inspired by visual prompt tuning, we use LPM to extract prompts for input images and hidden features at the encoder side and decoder side, respectively, which are fed as additional information into the Swin Transformer layer of a pre-trained transformer-based image compression model to affect the allocation of attention region and the bits, which in turn changes the target compression ratio of the model. To ensure the network is more lightweight, we involves the integration of prompt networks with less convolutional layers. Exhaustive experiments show that compared to methods based on multiple models, which are optimized separately for different target rates, the proposed method arrives at the same performance with 80% savings in parameter storage and 90% savings in datasets. Meanwhile, our model outperforms all current variable bitrate image methods in terms of rate-distortion performance and approaches the state-of-the-art fixed bitrate image compression methods trained from scratch

Contribution of vanishing mountain glaciers to global and regional terrestrial water storage changes

Mountain is called the water towers of the world. Due to high sensitivity and vulnerability to climate change, more attention is paid to the change of water resources in mountain regions, where provide water for environmental and human demands downstream. Mountains glacier, as one of the most important components of terrestrial water storage (TWS), effectively regulates and stabilizes surface water resources. TWS appears to be trending below previous ranges in recent years, and glacier retreating is becoming the primary cause of TWS depletion in mountain regions. However, how much mountain glacier changes contribute to TWS changes around mountain regions is unknown. Here, we combine multi-source datasets to quantify the contribution rate over high-elevation mountain regions. On a global scale, the glacial melting is equivalent to about 49% of the total TWS decline during 2006–2015. TWS and glacier show decreasing trends in most of mountain regions and watersheds of the Third Pole and surroundings (TPs), but the contribution ranges from −23% to 728% in mountain regions and −21% to 99% in watersheds of TPs. There are larger contributions in regions with more glaciers, while smaller in less glacier-covered regions. Glacier together with other storage components play diverse roles across different mountain regions and watersheds, but factors with great influence are glacier, groundwater, soil water, reservoirs and lakes

COVID-19 vaccination and the risk of autoimmune diseases: a Mendelian randomization study

BackgroundIn recent times, reports have emerged suggesting that a variety of autoimmune disorders may arise after the coronavirus disease 2019 (COVID-19) vaccination. However, causality and underlying mechanisms remain unclear.MethodsWe collected summary statistics of COVID-19 vaccination and 31 autoimmune diseases from genome-wide association studies (GWAS) as exposure and outcome, respectively. Random-effects inverse variance weighting (IVW), MR Egger, weighted median, simple mode, and weighted mode were used as analytical methods through Mendelian randomization (MR), and heterogeneity and sensitivity analysis were performed.ResultsWe selected 72 instrumental variables for exposure (p < 5 × 10−6; r2 < 0.001, genetic distance = 10,000 kb), and MR analyses showed that COVID-19 vaccination was causally associated with an increased risk of multiple sclerosis (MS) (IVW, OR: 1.53, 95% CI: 1.065–2.197, p = 0.026) and ulcerative colitis (UC) (IVW, OR: 1.00, 95% CI: 1.000–1.003, p = 0.039). If exposure was refined (p < 5 × 10−8; r2 < 0.001, genetic distance = 10,000 kb), the associations became negative. No causality was found for the remaining outcomes. These results were robust to sensitivity and heterogeneity analyses.ConclusionOur study provided potential evidence for the impact of COVID-19 vaccination on the risk of MS and UC occurrence, but it lacks sufficient robustness, which could provide a new idea for public health policy

A panther chameleon skin-inspired core@shell supramolecular hydrogel with spatially organized multi-luminogens enables programmable color change

Organization of different iridophores into a core@shell structure constitutes an evolutionary novelty for panther chameleons that allows their skins to display diverse color change. Inspired by this natural color-changing design, we present a responsive core@shell-structured multi-luminogen supramolecular hydrogel system that generates a programmable multi-color fluorescent change. Specifically, red Eu$^{3+}$-amidopicolinate (R) luminogen is incorporated into the core hydrogel, while blue naphthalimide (B) and green perylene-tetracarboxylic acid (G) luminogens are grown into two supramolecular shell hydrogels. The intensities of G/B luminogens could then be controlled independently, which enables its emission color to be programmed easily from red to blue or green, nearly covering the full visible spectrum. Because of the differential excitation energies between these luminogens, a desirable excitation wavelength-dependent fluorescence is also achieved. Colorful materials with a patterned core@shell structure are also demonstrated for anti-counterfeiting, opening up the possibility of utilizing a bioinspired core@shell structure to develop an efficient multi-color fluorescent system with versatile uses

Challenges of EGFR-TKIs in NSCLC and the potential role of herbs and active compounds: From mechanism to clinical practice

Epidermal growth factor receptor (EGFR) mutations are the most common oncogenic driver in non-small cell lung cancer (NSCLC). Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are widely used in the treatment of lung cancer, especially in the first-line treatment of advanced NSCLC, and EGFR-TKIs monotherapy has achieved better efficacy and tolerability compared with standard chemotherapy. However, acquired resistance to EGFR-TKIs and associated adverse events pose a significant obstacle to targeted lung cancer therapy. Therefore, there is an urgent need to seek effective interventions to overcome these limitations. Natural medicines have shown potential therapeutic advantages in reversing acquired resistance to EGFR-TKIs and reducing adverse events, bringing new options and directions for EGFR-TKIs combination therapy. In this paper, we systematically demonstrated the resistance mechanism of EGFR-TKIs, the clinical strategy of each generation of EGFR-TKIs in the synergistic treatment of NSCLC, the treatment-related adverse events of EGFR-TKIs, and the potential role of traditional Chinese medicine in overcoming the resistance and adverse reactions of EGFR-TKIs. Herbs and active compounds have the potential to act synergistically through multiple pathways and multiple mechanisms of overall regulation, combined with targeted therapy, and are expected to be an innovative model for NSCLC treatment

Passivation mechanism of thermal atomic layer-deposited Al2O3 films on silicon at different annealing temperatures

Thermal atomic layer-deposited (ALD) aluminum oxide (Al(2)O(3)) acquires high negative fixed charge density (Q(f)) and sufficiently low interface trap density after annealing, which enables excellent surface passivation for crystalline silicon. Q(f) can be controlled by varying the annealing temperatures. In this study, the effect of the annealing temperature of thermal ALD Al(2)O(3) films on p-type Czochralski silicon wafers was investigated. Corona charging measurements revealed that the Q(f) obtained at 300°C did not significantly affect passivation. The interface-trapping density markedly increased at high annealing temperature (>600°C) and degraded the surface passivation even at a high Q(f). Negatively charged or neutral vacancies were found in the samples annealed at 300°C, 500°C, and 750°C using positron annihilation techniques. The Al defect density in the bulk film and the vacancy density near the SiO(x)/Si interface region decreased with increased temperature. Measurement results of Q(f) proved that the Al vacancy of the bulk film may not be related to Q(f). The defect density in the SiO(x) region affected the chemical passivation, but other factors may dominantly influence chemical passivation at 750°C

Sestrin2 protects against hypoxic nerve injury by regulating mitophagy through SESN2/AMPK pathway

Hypoxia induced by high altitude can lead to severe neurological dysfunction. Mitophagy is known to play a crucial role in hypoxic nerve injury. However, the regulatory mechanism of mitophagy during this injury remains unclear. Recent studies have highlighted the role of Sestrin2 (SESN2), an evolutionarily conserved stress-inducible protein against acute hypoxia. Our study demonstrated that hypoxia treatment increased SESN2 expression and activated mitophagy in PC12 cells. Furthermore, the knock-out of Sesn2 gene led to a significant increase in mitochondrial membrane potential and ATP concentrations, which protected the PC12 cells from hypoxic injury. Although the AMPK/mTOR pathway was significantly altered under hypoxia, it does not seem to participate in mitophagy regulation. Instead, our data suggest that the mitophagy receptor FUNDC1 plays a vital role in hypoxia-induced mitophagy. Moreover, SESN2 may function through synergistic regulation with other pathways, such as SESN2/AMPK, to mediate cellular adaptation to hypoxia, including the regulation of mitophagy in neuron cells. Therefore, SESN2 plays a critical role in regulating neural cell response to hypoxia. These findings offer valuable insights into the underlying molecular mechanisms governing the regulation of mitophagy under hypoxia and further highlight the potential of SESN2 as a promising therapeutic target for hypoxic nerve injury