RemixFormer++: A Multi-modal Transformer Model for Precision Skin Tumor Differential Diagnosis with Memory-efficient Attention.

Diagnosing malignant skin tumors accurately at an early stage can be challenging due to ambiguous and even confusing visual characteristics displayed by various categories of skin tumors. To improve diagnosis precision, all available clinical data from multiple sources, particularly clinical images, dermoscopy images, and medical history, could be considered. Aligning with clinical practice, we propose a novel Transformer model, named Remix-Former++ that consists of a clinical image branch, a dermoscopy image branch, and a metadata branch. Given the unique characteristics inherent in clinical and dermoscopy images, specialized attention strategies are adopted for each type. Clinical images are processed through a top-down architecture, capturing both localized lesion details and global contextual information. Conversely, dermoscopy images undergo a bottom-up processing with two-level hierarchical encoders, designed to pinpoint fine-grained structural and textural features. A dedicated metadata branch seamlessly integrates non-visual information by encoding relevant patient data. Fusing features from three branches substantially boosts disease classification accuracy. RemixFormer++ demonstrates exceptional performance on four single-modality datasets (PAD-UFES-20, ISIC 2017/2018/2019). Compared with the previous best method using a public multi-modal Derm7pt dataset, we achieved an absolute 5.3% increase in averaged F1 and 1.2% in accuracy for the classification of five skin tumors. Furthermore, using a large-scale in-house dataset of 10,351 patients with the twelve most common skin tumors, our method obtained an overall classification accuracy of 92.6%. These promising results, on par or better with the performance of 191 dermatologists through a comprehensive reader study, evidently imply the potential clinical usability of our method.

Explorer: efficient DNA coding by De Bruijn graph toward arbitrary local and global biochemical constraints.

With the exponential growth of digital data, there is a pressing need for innovative storage media and techniques. DNA molecules, due to their stability, storage capacity, and density, offer a promising solution for information storage. However, DNA storage also faces numerous challenges, such as complex biochemical constraints and encoding efficiency. This paper presents Explorer, a high-efficiency DNA coding algorithm based on the De Bruijn graph, which leverages its capability to characterize local sequences. Explorer enables coding under various biochemical constraints, such as homopolymers, GC content, and undesired motifs. This paper also introduces Codeformer, a fast decoding algorithm based on the transformer architecture, to further enhance decoding efficiency. Numerical experiments indicate that, compared with other advanced algorithms, Explorer not only achieves stable encoding and decoding under various biochemical constraints but also increases the encoding efficiency and bit rate by ¿10%. Additionally, Codeformer demonstrates the ability to efficiently decode large quantities of DNA sequences. Under different parameter settings, its decoding efficiency exceeds that of traditional algorithms by more than two-fold. When Codeformer is combined with Reed-Solomon code, its decoding accuracy exceeds 99%, making it a good choice for high-speed decoding applications. These advancements are expected to contribute to the development of DNA-based data storage systems and the broader exploration of DNA as a novel information storage medium.

Curvature Regularization for Non-Line-of-Sight Imaging From Under-Sampled Data.

Non-line-of-sight (NLOS) imaging aims to reconstruct the three-dimensional hidden scenes by using time-of-flight photon information after multiple diffuse reflections. The under-sampled scanning data can facilitate fast imaging. However, the resulting reconstruction problem becomes a serious ill-posed inverse problem, the solution of which is highly likely to be degraded due to noises and distortions. In this paper, we propose novel NLOS reconstruction models based on curvature regularization, i.e., the object-domain curvature regularization model and the dual (signal and object)-domain curvature regularization model. In what follows, we develop efficient optimization algorithms relying on the alternating direction method of multipliers (ADMM) with the backtracking stepsize rule, for which all solvers can be implemented on GPUs. We evaluate the proposed algorithms on both synthetic and real datasets, which achieve state-of-the-art performance, especially in the compressed sensing setting. Based on GPU computing, our algorithm is the most effective among iterative methods, balancing reconstruction quality and computational time. All our codes and data are available at https://github.com/Duanlab123/CurvNLOS.

Test-retest reliability of the attention network test from the perspective of intrinsic network organization.

The attention network test (ANT), developed based on the triple-network taxonomy by Posner and colleagues, has been widely used to examine the efficacy of alerting, orienting and executive control in clinical and developmental neuroscience studies. Recent research suggests the imperfect reliability of the behavioural ANT and its variants. However, the classical ANT fMRI task's test-retest reliability has received little attention. Moreover, it remains ambiguous whether the attention-related intrinsic network components, especially the dorsal attention, ventral attention and frontoparietal network, manifest acceptable reliability. The present study approaches these issues by utilizing an openly available ANT fMRI dataset for participants with Parkinson's disease and healthy elderly. The reproducibility of group-level activations across sessions and participant groups and the test-retest reliability at the individual level were examined at the voxel, region and network levels. The intrinsic network was defined using the Yeo-Schaefer atlas. Our results reveal three critical facets: (1) the overlapping of the group-level contrast map between sessions and between participant groups was unsatisfactory; (2) the reliability of alerting, orienting and executive, defined as a contrast between conditions, was worse than estimates of specific conditions. (3) Dorsal attention, ventral attention, visual and somatomotor networks showed acceptable reliability for the congruent and incongruent conditions. Our results suggest that specific condition estimates might be used instead of the contrast map for individual or group-difference studies.

Aß1-42 stimulates an increase in autophagic activity through tunicamycin-induced endoplasmic reticulum stress in HTR-8/SVneo cells and late-onset pre-eclampsia.

Environmental changes can trigger endoplasmic reticulum (ER) stress and misfolded protein accumulation, potentially leading to pre-eclampsia (PE). Amyloid-ß (Aß) is a crucial misfolded protein that can overactivate autophagy. Our study assessed the expression of Aß1-42 and autophagic activity in PE placental tissues and trophoblasts under ER stress. Placental tissues were surgically collected from normal pregnant women (NP) and pregnant women with late-onset PE (LOPE) delivering through cesarean section. The expression levels of Aß1-42 were detected in both PE and NP placental tissues, as well as in tunicamycin (TM)-induced HTR-8/SVneo cells. Autophagy-related proteins, such as Beclin-1, the ratio of LC3-II to LC3-I, ATG5, and SQSTM1/p62 in the placental tissues and HTR-8/SVneo cells were measured by Western blot. The number and morphology of autophagosomes were observed using transmission electron microscopy (TEM). Potential targets associated with the unfolded protein response (UPR) in the placental tissues of NP and PE cases were screened using PCR Arrays. The misfolded protein was significantly upregulated in the PE group. In both PE placental tissues and TM-induced HTR-8/SVneo cells, not only was Aß1-42 upregulated, but also Beclin-1, ATG5, and LC3BII/I were significantly increased, accompanied by an increase in autophagosome count, while SQSTM1/P62 was downregulated. A total of 17 differentially expressed genes (DEGs) associated with the UPR were identified, among which elevated calnexin (CANX) was validated in the placenta from both PE and TM-induced HTR-8/SVneo cells. Autophagy is significantly upregulated in PE cases due to ER stress-induced Aß1-42 accumulation, likely mediated by autophagy-related proteins involved in the UPR.

A Large-Scale Online Survey on Clinical Severity and Associated Risk Factors for SARS-CoV-2 Omicron Infection - China, April-May 2023.

What is already known about this topic?: Individuals who initially contract severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lack significant mixed immunity. Therefore, it is crucial to monitor the clinical characteristics and associated factors of these individuals in order to inform policy-making. What is added by this report?: The common symptoms reported were fever, cough, and sore throat. Reinfections and receiving four vaccination doses within a 6-month period were found to be associated with a shorter duration of virus shedding, decreased hospitalization rate, and reduced risk of pneumonia. Individuals aged 60 years and older, as well as those with underlying medical conditions, had a higher risk of developing pneumonia. What are the implication for public health practices?: Online surveys conducted through social media platforms have the potential to complement disease surveillance and data collection efforts. In terms of vaccination prioritization, it is recommended to prioritize older individuals and those with underlying diseases.

Metamaterial Absorbers with Archimedean Tiling Structures: Toward Response and Absorption of Multiband Electromagnetic Waves.

With the continuous development of electromagnetic wave-absorbing materials, the design of artificial structures for electromagnetic absorbers based on the concept of metamaterials is becoming more abundant. However, in the design process, it is difficult to further broaden the effective absorption band due to the limitation that the traditional single-size structure responds to electromagnetic waves only in specific frequency bands. Therefore, in this paper, based on the moth-eye bionic hexagonal structure absorber with antireflection performance, an Archimedean tiling structure is designed to optimize it, and through the introduction of a variety of primitives with large differences in dimensions, a multifrequency band-response mechanism is achieved to enhance the multireflection mechanism, which can effectively broaden the absorption band and improve the wave absorption performance. Ultimately, the moth-eye bionic structure absorber optimized by (3.4.6.4) can achieve an effective absorption of 10.26 GHz at a thickness of 2 mm. This work presents a new idea for the design work of electromagnetic wave-absorbing metamaterials, which has a broad application prospect in the aerospace, electronic information countermeasures, communication, and detection industries.

Novel Local-Chiral Metamaterial: Effective Modulation of Amplitude & Phase for Wideband Polarization-Insensitive Absorption.

Metamaterial has received widespread research in the fields of electromagnetic stealth due to its characteristics of strong resonance and flexible designability. However, a lack of a comprehensive understanding of the internal physical mechanism still imposes certain limitations on broadband absorption designs. Hence, this work proposes a new strategy for the broadening of the working frequency band of metamaterial absorbers by constructing local-chiral features to regulate the amplitude and phase information. The absorber consists of staggered cut-wire metal patterns with lumped resistors placed at the center position determined by characteristic mode analysis. Combining the modal significance, equivalent circuit, surface current, electric field distribution, and symmetry model theory, the working mechanism for wideband absorption performance has been analyzed in detail. The experimental results are in good agreement with the simulation results; the absorption rate exceeds 82% in the frequency range of 4.5-11.7 GHz and surpasses about 90% in the frequency range of 4.7-10.8 GHz under transverse electric (TE) or transverse-magnetic (TM) polarizations. Compared to the case without chiral features, the proposed design can achieve a 28% increase in operating bandwidth. The proposed design method is applicable for the optimization of various typical dipole-type metamaterial absorbers and provides a novel strategy for future wideband metamaterial absorption.

Boosting Conductive Loss and Magnetic Coupling Based on "Size Modulation Engineering" toward Lower-Frequency Microwave Absorption.

The rational design of absorber size is a promising strategy for obtaining excellent electromagnetic wave (EMW) absorption performance. However, achieving controllable tuning of the material size through simple methods is challenging and the associated EMW attenuation mechanisms are still unclear. In this study, the sizes of metal-organic frameworks (MOFs) are successfully tailored by changing the growth time and the molar ratio of iron (Fe)/organic ligands. The lateral and vertical lengths of MOFs vary in the range of 200 nm to 2 µm and 100 nm to 1 µm, respectively. Both experiments and simulations confirm that the decrease of MOF size favors the formation of more conductive networks, which is beneficial for improving the conductivity loss. Meanwhile, the micromagnetic simulation reveals that the magnetic coupling can be effectively enhanced by the decrease of MOF size, which is conducive to the improvement of magnetic loss, especially in low-frequency range. The reflection loss of Fe-based MOFs with optimized size reaches -46.4 dB at 6.2 GHz with an effective absorption bandwidth of 3.1 GHz. This work illustrates the important role of size effect in EMW dissipation and provides an effective strategy for enhancing the low-frequency EMW absorption performance.

Joint 2D-3D cross-pseudo supervision for carotid vessel wall segmentation.

Introduction: The segmentation of the carotid vessel wall using black-blood magnetic resonance images was a crucial step in the diagnosis of atherosclerosis. The objective was to accurately isolate the region between the artery lumen and outer wall. Although supervised learning methods achieved remarkable accuracy in vessel segmentation, their effectiveness remained limited due to their reliance on extensive labeled data and human intervention. Furthermore, when confronted with three-dimensional datasets featuring insufficient and discontinuous label data, these learning-based approaches could lose their efficacy. In this paper, we proposed a novel Joint 2D-3D Cross-Pseudo Supervision (JCPS) method for accurate carotid vessel wall segmentation. Methods: In this study, a vascular center-of-gravity positioning module was developed to automatically estimate the region of blood vessels. To achieve accurate segmentation, we proposed a joint 2D-3D semi-supervised network to model the three-dimensional continuity of vascular structure. In addition, a novel loss function tailored for vessel segmentation was introduced, consisting of four components: supervision loss, cross-pseudo supervision loss, pseudo label supervision loss, and continuous supervision loss, all aimed at ensuring the accuracy and continuity of the vessel structure. In what followed, we also built up a user-friendly Graphical User Interface based on our JCPS method for end-users. Results: Our proposed JCPS method was evaluated using the Carotid Artery Vessel Wall Segmentation Challenge dataset to assess its performance. The experimental results clearly indicated that our approach surpassed the top 10 methods on the leaderboard, resulting in a significant enhancement in segmentation accuracy. Specifically, we achieved an average Dice similarity coefficient increase from 0.775 to 0.806 and an average quantitative score improvement from 0.837 to 0.850, demonstrating the effectiveness of our proposed JCPS method for carotid artery vessel wall segmentation. Conclusion: The experimental results suggested that the JCPS method had a high level of generalization performance by producing pseudo labels that were comparable with software annotations for data-imbalanced segmentation tasks.

Evaluating the accessibility and capacity of SARS-CoV-2 vaccination and analyzing convenience-related factors during the Omicron variant epidemic in Beijing, China.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination service system lacks standardized indicators to assess resource allocation. Moreover, data on specific vaccination-promoting measures is limited. This study aimed to evaluate vaccination accessibility and capacity and investigate convenience-related factors in China during the Omicron variant epidemic. We collected information on SARS-CoV-2 vaccination services among vaccination sites in Beijing. Analysis was performed using nearest neighbor, Ripley's K, hot spot analysis, and generalized estimating equations. Overall, 299 vaccination sites were included. The demand for the SARS-CoV-2 vaccine increased with the increase in daily new cases, and the number of staff administering vaccines should be increased in urban areas at the beginning of the epidemic. Providing vaccination for both children and adults, extending vaccination service hours, and offering a wider range of vaccine categories significantly increased the doses of vaccines administered (all P < .05). The provision of mobile vaccination vehicles effectively increased the doses of vaccines administered to individuals aged ≥ 60 years (P < .05). The allocation of SARS-CoV-2 vaccination services should be adjusted according to geographic location, population size, and vaccination demands. Simultaneous provision of vaccination services for children and their guardians, flexible service hours, prompt innovative vaccine production, and tailored vaccination strategies can foster vaccination uptake.

Clinical manifestations of respiratory syncytial virus infection and the risk of wheezing and recurrent wheezing illness: a systematic review and meta-analysis.

BACKGROUND: Respiratory syncytial virus (RSV) infection in infants is a global health priority. We aimed to investigate the common manifestations of RSV infection by age group and human development index (HDI) level and to assess its association with the development of wheezing and recurrent wheezing illness. METHODS: We searched the literature published between January 1, 2010 and June 2, 2022 in seven databases. Outcomes included common manifestations and long-term respiratory outcomes of RSV infection in children. Random- and fixed-effect models were used to estimate the effect size and their 95% confidence intervals. Subgroup analysis was conducted by age and HDI levels. This review was registered in PROSPERO (CRD42022379401). RESULTS: The meta-analysis included 47 studies. The top five manifestations were cough (92%), nasal congestion (58%), rhinorrhea (53%), shortness of breath (50%), and dyspnea (47%). The clinical symptoms were most severe in infants. In our analysis, compared to very high and high HDI countries, fewer studies in medium HDI countries reported related manifestations, and no study in low HDI countries reported that. The RSV-infected infants were more likely to develop wheezing than the non-infected infants [odds ratio (OR), 3.12; 95% CI, 2.59-3.76] and had a higher risk of developing wheezing illnesses after recovery (OR, 2.60; 95% CI, 2.51-2.70). CONCLUSIONS: Cough and shortness of breath are common manifestations of RSV infection. More attention should be given to infants and areas with low HDI levels. The current findings confirm an association between RSV infection and wheezing or recurrent wheezing illness.

Oribron: An Origami-Inspired Deformable Rigid Bronchoscope for Radial Support.

The structure of a traditional rigid bronchoscope includes proximal, distal, and body, representing an important means to treat hypoxic diseases. However, the body structure is too simple, resulting in the utilization rate of oxygen being usually low. In this work, we reported a deformable rigid bronchoscope (named Oribron) by adding a Waterbomb origami structure to the body. The Waterbomb's backbone is made of films, and the pneumatic actuators are placed inside it to achieve rapid deformation at low pressure. Experiments showed that Waterbomb has a unique deformation mechanism, which can transform from a small-diameter configuration (#1) to a large-diameter configuration (#2), showing excellent radial support capability. When Oribron entered or left the trachea, the Waterbomb remained in #1. When Oribron is working, the Waterbomb transforms from #1 to #2. Since #2 reduces the gap between the bronchoscope and the tracheal wall, it effectively slows down the rate of oxygen loss, thus promoting the absorption of oxygen by the patient. Therefore, we believe that this work will provide a new strategy for the integrated development of origami and medical devices.

Incidence, hospitalization, and mortality in children aged 5 years and younger with respiratory syncytial virus-related diseases: A systematic review and meta-analysis.

Objectives: Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infection in young children. We aimed to analyze the factors affecting the estimation of RSV-related disease burden, and to provide evidence to help establish a surveillance system. Methods: We searched the English- and Chinese-language databases for articles published between January 1, 2010 and June 2, 2022. The quality of the included articles was assessed using the Agency for Healthcare Research and Quality scale. Random-effects models were used for data synthesis and subgroup analyses. This review was registered in the Prospective Register of Systematic Reviews (PROSPERO: CRD42022372972). Results: We included 44 studies (149,321,171 participants), all of which were of medium or high quality. The pooled RSV-related disease incidence, hospitalization rate, in-hospital mortality, and overall mortality rates in children aged 5 years and younger were 9.0 per 100 children per year (95% confidence interval [CI]: 7.0-11.0), 1.7 per 100 children per year (95% CI: 1.3-2.1), 0.5 per 100 children per year (95% CI: 0.4-0.5), and 0.05 per 100 children per year (95% CI: 0.04-0.06), respectively. Age, economics, surveillance types, case definition, and data source were all recognized as influencing factors. Conclusions: A standardized and unified RSV surveillance system is required. Case definition and surveillance types should be fully considered for surveillance of different age groups.

Fast Multi-grid Methods for Minimizing Curvature Energies.

The geometric high-order regularization methods such as mean curvature and Gaussian curvature, have been intensively studied during the last decades due to their abilities in preserving geometric properties including image edges, corners, and contrast. However, the dilemma between restoration quality and computational efficiency is an essential roadblock for high-order methods. In this paper, we propose fast multi-grid algorithms for minimizing both mean curvature and Gaussian curvature energy functionals without sacrificing accuracy for efficiency. Unlike the existing approaches based on operator splitting and the Augmented Lagrangian method (ALM), no artificial parameters are introduced in our formulation, which guarantees the robustness of the proposed algorithm. Meanwhile, we adopt the domain decomposition method to promote parallel computing and use the fine-to-coarse structure to accelerate convergence. Numerical experiments are presented on image denoising, CT, and MRI reconstruction problems to demonstrate the superiority of our method in preserving geometric structures and fine details. The proposed method is also shown effective in dealing with large-scale image processing problems by recovering an image of size 1024×1024 within 40s, while the ALM method [1] requires around 200s.

Bioinspired multiple-degrees-of-freedom responsive metasurface by high-entropy-alloy ribbons with hierarchical nanostructures for electromagnetic wave absorption.

The compound eyes of the dragonfly, Pantala flavescens Fabricius, are covered by micro-scaled ocelli capable of sensing polarized light, an attractive property for radar stealth and counterreconnaissance. In this work, we fabricated biomimetic electromagnetic wave absorption materials (EAMs) by analyzing the covert information identifications of biological systems and focusing on the design of metastructures and microstructures. Several bionic metasurfaces with anisotropic double-V meta atoms made up of (FeCoNiSi8.9Al8.9)C0.2 high-entropy-alloy (HEA) ribbons for multiple-degrees-of-freedom recognition and broadband absorption are presented. The covert phase, amplitude, and angular momentum of electromagnetic waves were controlled and recognized as information by manipulating the rotation angle θ of meta atoms. A vortex wave with a topological charge of 1 was generated to recognize linearly polarization and left- and right-handed circular polarization. In addition, the polarization conversion enhanced absorption. The hierarchical nanostructures of HEA ribbons give rise to suitable electromagnetic loss and a superior impedance match. Finally, inspired by the structure of compound eyes, the designed multilayer metamaterials realized effective absorption (reflection loss (RL) ≤  - 10 dB) within the 4.5-18 GHz regime under 2.8 mm thickness. These materials provide evidence for a new way for integrated EAMs and metamaterials.

Two-Dimensional Basalt/Ni Microflakes with Uniform and Compact Nanolayers for Optimized Microwave Absorption Performance.

It has been accepted that the uniform distribution of magnetic metal particles is beneficial to microwave absorption, while why the homogeneous magnetic particles on the dielectric substrate improve the electromagnetic loss is still unclear. Herein, metal Ni nanoparticles, two-dimensional (2D) basalt/scattered Ni, and basalt/uniform Ni microflakes are obtained through a pretreatment and electroless deposition process. In comparison to Ni nanoparticles and basalt/scattered Ni, the basalt/Ni microflakes with largely uniform and compact Ni nanolayers on basalt, breaking the percolation limit, are favorable for enhanced electromagnetic attenuation. The Ni nanolayers are convenient for construction of a microscale conductive net and migration of an electron. The 2D heterostructures constructed by basalt substrates and decorated Ni layers boost multiple scattering absorption and promote interfacial polarization. Meanwhile, exposed Ni does not inhibit magnetic resonance, enabling strong magnetic coupling. Consequently, the basalt/Ni microflakes with uniform Ni nanolayers demonstrate better microwave absorption with a minimum reflection loss of -30 dB and an effective absorption bandwidth of 3 GHz at 1 mm. This work shows that the uniform and compact magnetic metal nanolayers are effective in improving the dielectric loss and magnetic loss simultaneously to achieve the high-performance microwave absorption.

DVS-Net: Dual-domain Variable Splitting Network for Accelerated Parallel MRI Data.

Parallel imaging is an important method to accel-erate the acquisition of magnetic resonance imaging data, which can shorten the breath-hold times and reduce motion artifacts. In this paper, we propose a joint frequency domain and image domain (dual-domain) reconstruction method by introducing the full sampling condition for the undersampled multi-coil MR data. The motivation is that the dual domain method can provide more information for accurate image reconstruction. An efficient iterative algorithm is developed based on the variable splitting technique and alternating direction method of multipliers, which is unrolled into an end-to-end trainable deep neural network. We evaluate the proposed network on complex valued multi-coil knee images for both 6-fold and 8-fold acceleration factors, and compare with both variational and deep learning based reconstruction algorithms. The numerical results demonstrate that our method provides better reconstruction accuracy and perceptual quality by making using of the dual domain information. Clinical relevance: This improves the reconstruction quality for accelerated parallel MRI data both visually and quantitatively.