Stereoselective Synthesis of Polysubstituted Conjugated Dienes Enabled by Photo-Driven Sequential Sigmatropic Rearrangement.

We here reported a highly stereoselective method for the synthesis of polysubstituted conjugated dienes from α-aryl α-diazo alkynyl ketones and pyrazole-substituted unsymmetric aminals under mild conditions, which was promoted by photo-irridation and involved with 1,6-dipolar intermediate and quadruple sigmatropic rearrangements, was successfully developed. In this transformation, the cleavage of four bonds and the recombination of five bonds were implemented in one operational step. This protocol provided a modular tool for constructing dienes from amines, pyrazoles and α-alkynyl-α-diazoketones in one-pot manner. The results of mechanistic investigation indicated that the plausible reaction path underwent the 1,6-sigmatropic rearrangement instead of the 1,5-sigmatropic rearrangement.

Rationally Designed ZnTe@C Nanowires with Superior Zinc Storage Performance for Aqueous Zn Batteries.

Te-based materials with excellent electrical conductivity and ultra-high volume specific capacity have attracted much attention for the cost-efficient aqueous Zn batteries. However, the construction of functional structures with mild volume expansion and suppressed shuttle effects, enabling an expanded lifespan, is still a challenge for conversion-type materials. Herein, the carbon-coated zinc telluride nanowires (ZnTe@C NWs) are rationally designed as a high-performance cathode material for aqueous Zn batteries. The carbon-coated1D nanostructure could not only provide optimized transmission path for electrons and ions, but also help to maintain structure integrity upon volume variation and suppress intermediates dissolution, endowing the ZnTe@C NWs with improved cycling stability and reaction kinetics. Consequently, a reversible six-electron reaction mechanism of ZnTe@C NWs based on Te2- /Te4+ conversion with excellent output capacity (586 mAh g-1 at 0.1 A g-1 ) and lifespan (>250 mAh g-1 retained for 400 cycles at 1 A g-1 ) is eventually achieved.

NIR-II-Responsive CeO2-x@HA Nanotheranostics for Photoacoustic Imaging-Guided Sonodynamic-Enhanced Synergistic Phototherapy.

The therapeutic effect of photothermal therapy (PTT) and photodynamic therapy (PDT) is severely limited because of the shallow tissue penetration depth of the first near-infrared (NIR-I) light. Multifunctional nanotheranostics irradiated by the second near-infrared (NIR-II) light have received wide interest with respect to deeper tissue penetration, and sonodynamic therapy (SDT) synergistic phototherapy can achieve the complete elimination of tumors. Herein, we successfully constructed a single NIR-II light-induced nanotheranostic using cerium oxide (CeO2-x) with abundant oxygen vacancies for photoacoustic imaging-guided SDT-enhanced phototherapy for the first time. CeO2-x with surface crystalline disorder showed extensive NIR-II region absorption and an outstanding photothermal conversion ability. In addition, the CeO2-x layer with numerous oxygen defects can promote the separation of holes and electrons by ultrasound irradiation, which can remarkably enhance the efficacy of phototherapy to achieve high-efficiency tumor ablation. CeO2-x was surface modified with hyaluronic acid (HA) to prepare CeO2-x@HA to allow active tumor targeting efficiency. Both cell and animal experiments confirmed that all-in-one CeO2-x@HA exhibited a high therapeutic efficacy of SDT-enhanced PDT/PTT under 1064 nm laser irradiation, which achieved complete tumor eradication without systemic toxicity. This study significantly broadened the application of NIR-II-responsive CeO2-x for photoacoustic imaging-mediated SDT-enhanced phototherapy to the highly efficient and precise elimination of tumors.

Boosting Cathode Activity and Anode Stability of Zn-S Batteries in Aqueous Media Through Cosolvent-Catalyst Synergy.

Aqueous Zn-S battery with high energy density represents a promising large-scale energy storage technology, but its application is severely hindered by the poor reversibility of both S cathode and Zn anode. Herein, we develop a "cocktail optimized" electrolyte containing tetraglyme (G4) and water as co-solvents and I2 as additive. The G4-I2 synergy could activate efficient polar I3 - /I- catalyst couple and shield the cathode from water, thus facilitating the conversion kinetics of S and suppressing the interfacial side reactions. Simultaneously, it could stabilize Zn anode by forming an organic-inorganic interphase upon cycling. With boosted electrodes reversibility, the Zn-S cell delivers a high capacity of 775 mAh g-1 at 2 A g-1 , and retains over 70 % capacity after 600 cycles at 4 A g-1 . The advances can also be readily generalized to other ethers/water hybrid electrolytes, showing the universality of the "cocktail optimized" electrolyte design strategy.

Exploring the phytoremediation potential of water hyacinth by FTIR Spectroscopy and ICP-OES for treatment of heavy metal contaminated water.

Toxic heavy metal pollution of water is a major environmental problem and the current remediation approaches are not optimal as they are non-eco-friendly and lacking in efficiency. As such phytoremediation, a green remediation technology is recognized as a better approach. In this study, both Fourier Transform Infrared (FTIR) Spectroscopy and Inductive Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) were used to investigate the capability of an aquatic plant, water hyacinth (Eichhornia crassipes) to remove heavy metals of lead, copper, cadmium and arsenic from aqueous solution at concentrations of 2 mg/L and 8 mg/L. Overall, the results showed that the uptake was rapid with the plants removing >80% of all the heavy metals at both concentrations. This uptake was proven by the detection of metal accumulation in plant tissues. Roots proved to be better accumulator than leaves. Maximum bioconcentration factor values indicating that the plant is a hyperaccumulator for lead and a moderate accumulator for the other heavy metals. Ligands such as O-H, C-O, C-C and C-H were found to aid the plant in accumulating heavy metal in its tissues. This study concludes that water hyacinth can be utilized as a phytoremediation agent to clean up heavy metal polluted water.

Insight into the fate of antibiotic resistance genes and bacterial community in co-composting green tea residues with swine manure.

Green tea residues (GTRs) are byproducts of tea production and processing, and this type of agricultural waste retains nutritious components. This study investigated the co-composting of GTRs with swine manure, as well as the effects of GTRs on antibiotic resistance genes (ARGs) and the bacterial community during co-composting. The temperature and C/N ratio indicate compost was mature after processing. The addition of GTRs effectively promoted the reduction in the abundances of most targeted ARGs (tet and sul genes), mobile genetic element (MGE; intI1), and metal resistance genes (MRGs; pcoA and tcrB). Redundancy analysis (RDA) showed that GTRs can reduce the abundance of MRGs and ARGs by reducing the bioavailability of heavy metals. Network analysis shows that Firmicutes and Actinobacteria were the main hosts of ARGs and ARGs, MGEs, and MRGs shared the same potential host bacteria. Adding GTRs during composting may reduce ARGs transmission through horizontal gene transfer (HGT). GTRs affected the bacterial community, thereby influencing the variations in the ARG profiles and reducing the potential risk associated with the compost product.

Microstructural integrity of corticospinal and medial lemniscus tracts: insights from diffusion tensor tractography of right-hand amputees.

Reductions in sensory and motor activity following unilateral upper limb amputation during adulthood are associated with widespread, activity-dependent reorganization of the gray matter and white matter through the central nervous system. Likewise, in cases of congenital limb absence there is evidence that limited afferent or efferent activity affects the structural integrity of white matter pathways serving the affected side. Evidence that the structural integrity of mature sensory and motor tracts controlling the lost upper limb exhibits similar activity dependence is, however, sparse and inconsistent. Here we used diffusion tensor tractography to test whether amputation of the dominant right hand during adulthood (n = 16) alters the microstructural integrity of the major sensory (medial lemniscus, ML) and motor (corticospinal tract, CST) pathways controlling missing hand function. Consistent with prior findings, healthy control subjects (n = 27) exhibited higher fractional anisotropy (FA), an index of white matter microstructural integrity, within dominant left CST and nondominant right ML. Critically, in contrast to what might be expected if the microstructural organization of these tracts is activity dependent, these asymmetries persisted in amputees. Moreover, we failed to detect any differences in dominant left ML or CST between healthy control subjects and amputees. Our results are consistent with these white matter tracts being robust to changes in activity once mature or that continued use of the residual limb (in a compensatory fashion or with prosthesis) provides stimulation sufficient to maintain tract integrity. NEW & NOTEWORTHY We report that unilateral hand amputation in adults has no significant effects on the structure of major sensory or motor pathways contralateral to the amputation. Our results are consistent with the organization of these white matter tracts being robust to changes in activity once mature or that continued use of the residual limb (with or without a prosthesis) provides stimulation sufficient to maintain tract integrity.

Topical Spilanthol Inhibits MAPK Signaling and Ameliorates Allergic Inflammation in DNCB-Induced Atopic Dermatitis in Mice.

Atopic dermatitis (AD) is a recurrent allergic skin disease caused by genetic and environmental factors. Patients with AD may experience immune imbalance, increased levels of mast cells, immunoglobulin (Ig) E and pro-inflammatory factors (Cyclooxygenase, COX-2 and inducible NO synthase, iNOS). While spilanthol (SP) has anti-inflammatory and analgesic activities, its effect on AD remains to be explored. To develop a new means of SP, inflammation-related symptoms of AD were alleviated, and 2,4-dinitrochlorobenzene (DNCB) was used to induce AD-like skin lesions in BALB/c mice. Histopathological analysis was used to examine mast cells and eosinophils infiltration in AD-like skin lesions. The levels of IgE, IgG1 and IgG2a were measured by enzyme-linked immunosorbent assay (ELISA) kits. Western blot was used for analysis of the mitogen-activated protein kinase (MAPK) pathways and COX-2 and iNOS protein expression. Topical SP treatment reduced serum IgE and IgG2a levels and suppressed COX-2 and iNOS expression via blocked mitogen-activated protein kinase (MAPK) pathways in DNCB-induced AD-like lesions. Histopathological examination revealed that SP reduced epidermal thickness and collagen accumulation and inhibited mast cells and eosinophils infiltration into the AD-like lesions skin. These results indicate that SP may protect against AD skin lesions through inhibited MAPK signaling pathways and may diminish the infiltration of inflammatory cells to block allergic inflammation.

Magnetic resonance spectroscopy of current hand amputees reveals evidence for neuronal-level changes in former sensorimotor cortex.

Deafferentation is accompanied by large-scale functional reorganization of maps in the primary sensory and motor areas of the hemisphere contralateral to injury. Animal models of deafferentation suggest a variety of cellular-level changes including depression of neuronal metabolism and even neuronal death. Whether similar neuronal changes contribute to patterns of reorganization within the contralateral sensorimotor cortex of chronic human amputees is uncertain. We used functional MRI-guided proton magnetic resonance spectroscopy to test the hypothesis that unilateral deafferentation is associated with lower levels of N-acetylaspartate (NAA, a putative marker of neuronal integrity) in the sensorimotor hand territory located contralateral to the missing hand in chronic amputees (n = 19) compared with the analogous hand territory of age- and sex-matched healthy controls (n = 28). We also tested whether former amputees [i.e., recipients of replanted (n = 3) or transplanted (n = 2) hands] exhibit NAA levels that are indistinguishable from controls, possible evidence for reversal of the effects of deafferentation. As predicted, relative to controls, current amputees exhibited lower levels of NAA that were negatively and significantly correlated with the time after amputation. Contrary to our prediction, NAA levels in both replanted and transplanted patients fell within the range of the current amputees. We suggest that lower levels of NAA in current amputees reflects altered neuronal integrity consequent to chronic deafferentation. Thus local changes in NAA levels may provide a means of assessing neuroplastic changes in deafferented cortex. Results from former amputees suggest that these changes may not be readily reversible through reafferentation.NEW & NOTEWORTHY This study is the first to use functional magnetic resonance-guided magnetic resonance spectroscopy to examine neurochemical mechanisms underlying functional reorganization in the primary somatosensory and motor cortices consequent to upper extremity amputation and its potential reversal through hand replantation or transplantation. We provide evidence for selective alteration of cortical neuronal integrity associated with amputation-related deafferentation that may not be reversible.

Tract-based evaluation of white matter damage in individuals with early-treated phenylketonuria.

Previous research has documented white matter abnormalities in the brains of individuals with early-treated phenylketonuria (ETPKU). The majority of these past studies have relied on a region-based approach which focused on a limited number of spatially-defined regions within the brain. In the present study, we used diffusion tensor imaging (DTI) in conjunction with tract-based spatial statistics (TBSS) to perform an extensive examination of white matter tracts in the brains of ten individuals with ETPKU (mean age = 23.2 years) and 12 healthy non-PKU individuals (mean age = 23.5 years). Consistent with past research, we found that mean diffusivity (MD) was significantly restricted in the ETPKU group, and fractional anisotropy (FA) was comparable between the ETPKU and non-PKU groups. Moreover, we found restricted axial diffusivity (AD) and radial diffusivity (RD) in our ETPKU in numerous white matter tracts, suggesting widespread white matter compromise in ETPKU. In addition, this white matter pathology was more evident in older ETPKU participants with higher blood phenylalanine (phe) levels as compared to younger participants with lower phe levels.

Flexible Wearable Electrochemical Sensors Based on AuNR/PEDOT:PSS for Simultaneous Monitoring of Levodopa and Uric Acid in Sweat.

As a facile substitute for the invasive technique of blood testing, wearable electrochemical sensors exhibit high potential for the noninvasive and real-time monitoring of biomarkers in human sweat. However, owing to enzyme specificity, the simultaneous detection of multiple biomarkers by enzymatic analysis is challenging. Moreover, sweat accumulation under sensors causes sweat contamination, which hinders real-time biomarker detection from sweat. This study reports the design and fabrication of flexible wearable electrochemical sensors containing a composite comprising Au nanorods (AuNRs) and poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) for the nonenzymatic detection of levodopa (LD) and uric acid (UA) in sweat. Each sensor was integrated with a flexible three-electrode system and a microfluidic patch for sweat sampling. AuNRs immobilized by PEG-doped PEDOT:PSS showed excellent analytical performance for LD and UA at different potentials. Thus, the newly fabricated sensors could detect LD and UA over a broad detection range with high sensitivity and showed a low limit of detection for both species. On-body assessments confirmed the ability of these sensors to simultaneously detect LD and UA in real time. Therefore, this study could open new frontiers in the fabrication of wearable electrochemical sensors for the pharmacokinetic profile tracking of LD and gout management.

A topical VAEGAN-IHMM approach for automatic story segmentation.

Feature representations with rich topic information can greatly improve the performance of story segmentation tasks. VAEGAN offers distinct advantages in feature learning by combining variational autoencoder (VAE) and generative adversarial network (GAN), which not only captures intricate data representations through VAE's probabilistic encoding and decoding mechanism but also enhances feature diversity and quality via GAN's adversarial training. To better learn topical domain representation, we used a topical classifier to supervise the training process of VAEGAN. Based on the learned feature, a segmentor splits the document into shorter ones with different topics. Hidden Markov model (HMM) is a popular approach for story segmentation, in which stories are viewed as instances of topics (hidden states). The number of states has to be set manually but it is often unknown in real scenarios. To solve this problem, we proposed an infinite HMM (IHMM) approach which utilized an HDP prior on transition matrices over countably infinite state spaces to automatically infer the state's number from the data. Given a running text, a Blocked Gibbis sampler labeled the states with topic classes. The position where the topic changes was a story boundary. Experimental results on the TDT2 corpus demonstrated that the proposed topical VAEGAN-IHMM approach was significantly better than the traditional HMM method in story segmentation tasks and achieved state-of-the-art performance.

Improved microcalcification visualization using dual-energy digital mammography.

BACKGROUND: Dual-energy digital mammography (DEDM), involving a combination of high-energy (HE) and low-energy (LE) images, has been investigated as offering a potential improvement in microcalcification detection obscured by overlapping tissue structures. PURPOSE: To explore the possibility to improve detection of microcalcifications using the DEDM technique. MATERIAL AND METHODS: Three DEDM protocols were performed by adjusting the effective tube current time product (mAs) of LE image at the same (100%), one half (50%), and one-quarter (25%) of that used in HE image acquisition, named DEDM100%, DEDM50%, and DEDM25%, respectively. A single-energy digital mammography (SEDM) method was also used as a control. A total of 525 regions of interest (ROIs) were used to compare the performance of the DEDM to that of SEDM using free-response receiver-operating characteristic (FROC) and areas under the FROC curve (Az). RESULTS: All DEDM protocols ranked significantly higher than the SEDM method (P < 0.001). The true-positive fraction was 0.90 for an average of 0.017-0.042 false-positive per image using the DEDM100%, 0.017-0.114 using the DEDM50%, 0.021-0.148 using the DEDM25%, and 0.134-0.422 using the SEDM. The estimated Az values were 0.915-0.940, 0.867-0.935, 0.824-0.930, and 0.567-0.673, respectively. CONCLUSION: The DEDM50% protocol provided a trade-off benefit between accurate microcalcification detectability and radiation dose for any tissue density. Therefore, the DEDM50% has the potential to minimize excess radiation dose without a negative impact on image quality which could improve earlier diagnosis of breast cancer.

Chaotic medical image encryption method using attention mechanism fusion ResNet model.

Introduction: With the rapid advancement of artificial intelligence (AI) technology, the protection of patient medical image privacy and security has become a critical concern in current research on image privacy protection. However, traditional methods for encrypting medical images have faced criticism due to their limited flexibility and inadequate security. To overcome these limitations, this study proposes a novel chaotic medical image encryption method, called AT-ResNet-CM, which incorporates the attention mechanism fused with the ResNet model. Methods: The proposed method utilizes the ResNet model as the underlying network for constructing the encryption and decryption framework. The ResNet's residual structure and jump connections are employed to effectively extract profound information from medical images and expedite the model's convergence. To enhance security, the output of the ResNet model is encrypted using a logistic chaotic system, introducing randomness and complexity to the encryption process. Additionally, an attention mechanism is introduced to enhance the model's response to the region of interest within the medical image, thereby strengthening the security of the encrypted network. Results: Experimental simulations and analyses were conducted to evaluate the performance of the proposed approach. The results demonstrate that the proposed method outperforms alternative models in terms of encryption effectiveness, as indicated by a horizontal correlation coefficient of 0.0021 and information entropy of 0.9887. Furthermore, the incorporation of the attention mechanism significantly improves the encryption performance, reducing the horizontal correlation coefficient to 0.0010 and increasing the information entropy to 0.9965. These findings validate the efficacy of the proposed method for medical image encryption tasks, as it offers enhanced security and flexibility compared to existing approaches. Discussion: In conclusion, the AT-ResNet-CM method presents a promising solution to address the limitations of traditional encryption techniques in protecting patient medical images. By leveraging the attention mechanism fused with the ResNet model, the method achieves improved security and flexibility. The experimental results substantiate the superiority of the proposed method in terms of encryption effectiveness, horizontal correlation coefficient, and information entropy. The proposed method not only addresses the shortcomings of traditional methods but also provides a more robust and reliable approach for safeguarding patient medical image privacy and security.

Remote sensing traffic scene retrieval based on learning control algorithm for robot multimodal sensing information fusion and human-machine interaction and collaboration.

In light of advancing socio-economic development and urban infrastructure, urban traffic congestion and accidents have become pressing issues. High-resolution remote sensing images are crucial for supporting urban geographic information systems (GIS), road planning, and vehicle navigation. Additionally, the emergence of robotics presents new possibilities for traffic management and road safety. This study introduces an innovative approach that combines attention mechanisms and robotic multimodal information fusion for retrieving traffic scenes from remote sensing images. Attention mechanisms focus on specific road and traffic features, reducing computation and enhancing detail capture. Graph neural algorithms improve scene retrieval accuracy. To achieve efficient traffic scene retrieval, a robot equipped with advanced sensing technology autonomously navigates urban environments, capturing high-accuracy, wide-coverage images. This facilitates comprehensive traffic databases and real-time traffic information retrieval for precise traffic management. Extensive experiments on large-scale remote sensing datasets demonstrate the feasibility and effectiveness of this approach. The integration of attention mechanisms, graph neural algorithms, and robotic multimodal information fusion enhances traffic scene retrieval, promising improved information extraction accuracy for more effective traffic management, road safety, and intelligent transportation systems. In conclusion, this interdisciplinary approach, combining attention mechanisms, graph neural algorithms, and robotic technology, represents significant progress in traffic scene retrieval from remote sensing images, with potential applications in traffic management, road safety, and urban planning.

Pt/MXene-Based Flexible Wearable Non-Enzymatic Electrochemical Sensor for Continuous Glucose Detection in Sweat.

Wearable non-invasive sensors facilitate the continuous measurement of glucose in sweat for the treatment and management of diabetes. However, the catalysis of glucose and sweat sampling are challenges in the development of efficient wearable glucose sensors. Herein, we report a flexible wearable non-enzymatic electrochemical sensor for continuous glucose detection in sweat. We synthesized a catalyst (Pt/MXene) by the hybridization of Pt nanoparticles onto MXene (Ti3C2Tx) nanosheets with a broad linear range of glucose detection (0-8 mmol/L) under neutral conditions. Furthermore, we optimized the structure of the sensor by immobilizing Pt/MXene with a conductive hydrogel to enhance the stability of the sensor. Based on Pt/MXene and the optimized structure, we fabricated a flexible wearable glucose sensor by integrating a microfluidic patch for sweat collection onto a flexible sensor. We evaluated the utility of the sensor for the detection of glucose in sweat, and the sensor could detect the glucose change with the replenishment and consumption of energy by the body, and a similar trend was observed in the blood. An in vivo glucose test in sweat indicated that the fabricated sensor is promising for the continuous measurement of glucose, which is essential for the treatment and management of diabetes.

Self-supervised Signal Denoising for Magnetic Particle Imaging.

Magnetic particle imaging (MPI) is a medical imaging technology with high resolution and high sensitivity, which tracks the distribution of superparamagnetic iron oxide nanoparticles (SPIONs) in the nonlinear response to dynamic excitation at a field-free region. However, various noises distort the signals resulting in a decline in imaging quality. Traditional threshold-based methods cannot remove dynamic noise in MPI signals. Therefore, a self-supervised denoising method is proposed to denoise MPI signals in this study. The approach adopted U-net as the backbone and modified the network for MPI signals. The network is trained using two periods of noisy signals and the shape prior knowledge of the MPI signals is introduced for promoting the convergence of the self-supervised net. The experiments show that the learning-based method can still denoising the MPI signal without labeling data and eventually improve image quality, and our approach can achieve the best performance compared with other self-supervised methods in MPI signal denoising.

Feasibility study for the improvement of microcalcification visualization in different breast thicknesses and tissue components using a dual-energy approach in digital mammography.

OBJECTIVE: The purpose of this study was to improve detectability of microcalcifications using a dual-energy digital mammographic (DEDM) technique. METHODS: Slabs of uniform breast-equivalent plastic and an additional plate were used to mimic various breast thicknesses, from 3 to 7 cm, and to simulate microcalcification with diameters from 0.16 to 0.39 mm. Free-response receiver operating characteristics and area under the curves (Az) were used to evaluate the sensitivity of detecting microcalcifications using the DEDM compared with using the conventional single-energy digital mammography (SEDM). RESULTS: The mean number of false-positives per image was 0.0198 (Az = 0.956 ± 0.027) using DEDM compared with 0.292 (Az = 0.681 ± 0.235) using SEDM. A lower radiation dose could be possibly obtained for the DEDM technique with a thickness of less than 5 cm compared with the SEDM with a thickness larger than 5 cm. CONCLUSIONS: Microcalcifications could be more accurately and efficiently detected using the DEDM, which might bring reliable and promising applications on early computer-aided diagnosis of breast cancer.

Unusual imaging features of completely isolated enteric duplication in a child.

We report a case of completely isolated enteric duplication in an 18-month-old boy in whom US revealed a reniform abdominal mass with a pseudokidney sign that had no connection to adjacent organs. Distinctive histopathological changes of the duplication account for these unusual imaging features. Our case represents a diagnostic challenge in this rare entity. To our knowledge, this is a unique case.

Multilevel 2-D Quantum Wavelet Transforms.

Wavelet transform is being widely used in classical image processing. One-dimension quantum wavelet transforms (QWTs) have been proposed. Generalizations of the 1-D QWT into multilevel and multidimension have been investigated but restricted to the quantum wavelet packet transform (QWPTs), which is the direct product of 1-D QWPTs, and there is no transform between the packets in different dimensions. A 2-D QWT is vital for image processing. We construct the multilevel 2-D QWT's general theory. Explicitly, we built multilevel 2-D Haar QWT and the multilevel Daubechies D4 QWT, respectively. We have given the complete quantum circuits for these wavelet transforms, using both noniterative and iterative methods. Compared to the 1-D QWT and wavelet packet transform, the multilevel 2-D QWT involves the entanglement between components in different degrees. Complexity analysis reveals that the proposed transforms offer exponential speedup over their classical counterparts. Also, the proposed wavelet transforms are used to realize quantum image compression. Simulation results demonstrate that the proposed wavelet transforms are significant and obtain the same results as their classical counterparts with an exponential speedup.