Tethered peptide activation mechanism of the adhesion GPCRs ADGRG2 and ADGRG4.

Adhesion G protein-coupled receptors (aGPCRs) constitute an evolutionarily ancient family of receptors that often undergo autoproteolysis to produce α and ß subunits1-3. A tethered agonism mediated by the 'Stachel sequence' of the ß subunit has been proposed to have central roles in aGPCR activation4-6. Here we present three cryo-electron microscopy structures of aGPCRs coupled to the Gs heterotrimer. Two of these aGPCRs are activated by tethered Stachel sequences-the ADGRG2-ß-Gs complex and the ADGRG4-ß-Gs complex (in which ß indicates the ß subunit of the aGPCR)-and the other is the full-length ADGRG2 in complex with the exogenous ADGRG2 Stachel-sequence-derived peptide agonist IP15 (ADGRG2(FL)-IP15-Gs). The Stachel sequences of both ADGRG2-ß and ADGRG4-ß assume a U shape and insert deeply into the seven-transmembrane bundles. Constituting the FXφφφXφ motif (in which φ represents a hydrophobic residue), five residues of ADGRG2-ß or ADGRG4-ß extend like fingers to mediate binding to the seven-transmembrane domain and activation of the receptor. The structure of the ADGRG2(FL)-IP15-Gs complex reveals the structural basis for the improved binding affinity of IP15 compared with VPM-p15 and indicates that rational design of peptidic agonists could be achieved by exploiting aGPCR-ß structures. By converting the 'finger residues' to acidic residues, we develop a method to generate peptidic antagonists towards several aGPCRs. Collectively, our study provides structural and biochemical insights into the tethered activation mechanism of aGPCRs.

Membrane protein isolation and structure determination in cell-derived membrane vesicles.

Integral membrane protein structure determination traditionally requires extraction from cell membranes using detergents or polymers. Here, we describe the isolation and structure determination of proteins in membrane vesicles derived directly from cells. Structures of the ion channel Slo1 from total cell membranes and from cell plasma membranes were determined at 3.8 Å and 2.7 Å resolution, respectively. The plasma membrane environment stabilizes Slo1, revealing an alteration of global helical packing, polar lipid, and cholesterol interactions that stabilize previously unresolved regions of the channel and an additional ion binding site in the Ca2+ regulatory domain. The two methods presented enable structural analysis of both internal and plasma membrane proteins without disrupting weakly interacting proteins, lipids, and cofactors that are essential to biological function.

Correlation between structure and function in phosphatidylinositol lipid-dependent Kir2.2 gating.

SignificancePhosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) levels regulate cell membrane voltage by gluing two halves of a K+ channel together and opening the pore. PI(4)P competes with this process. Because both of these lipids are relatively abundant in the plasma membrane and are directly interconvertible through the action of specific enzymes, they may function together to regulate channel activity.

Establishing an Ion-Sieving Separator by Depositing Oxygen-Deficient SiOx Layer for Stabilized Zinc Metal Anode.

Stable plating/stripping of Zn metal anode remains a great challenge owing to uncontrollable dendrite growth and side reactions. Ion-sieving separators is a unique and promising solution, that possess Zn2+ permeability and promote Zn2+ transport, can effectively alleviate the abovementioned problems. Ion-sieving on glass fiber separator by deposition of oxygen-deficient SiOx layer via active screen plasma technology is achieved. While having chemical composition similar to the glass fiber, the SiOx nanoparticles contain oxygen-rich vacancies that promoted dissociation of the adsorbed water and generation of the hydroxyl groups. The negatively-charged hydroxylated SiOx layer can repel SO4 2- and attract Zn2+, which can alleviate the side reactions. The strong interplay between hydroxyl groups and Zn2+ can boost Zn affinity and yield fast Zn2+ transport. Consequently, the SiOx-deposited GF separator enabled dendrite-free Zn deposition morphology, which displays lower overpotential of 18 mV and longer cycling life over 2000 h for Zn symmetric cell. Such a separator can also be easily scaled up to prepare the high-performance large-area (4 × 6 cm2) pouch Zn-based devices, showing remarkable flexibility and practicality.

Screening for functional circular RNAs using the CRISPR-Cas13 system.

Circular RNAs (circRNAs) produced from back-spliced exons are widely expressed, but individual circRNA functions remain poorly understood owing to the lack of adequate methods for distinguishing circRNAs from cognate messenger RNAs with overlapping exons. Here, we report that CRISPR-RfxCas13d can effectively discriminate circRNAs from mRNAs by using guide RNAs targeting sequences spanning back-splicing junction (BSJ) sites featured in RNA circles. Using a lentiviral library that targets sequences across BSJ sites of highly expressed human circRNAs, we show that a group of circRNAs are important for cell growth mostly in a cell-type-specific manner and that a common oncogenic circRNA, circFAM120A, promotes cell proliferation by preventing the mRNA for family with sequence similarity 120A (FAM120A) from binding the translation inhibitor IGF2BP2. Further application of RfxCas13d-BSJ-gRNA screening has uncovered circMan1a2, which has regulatory potential in mouse embryo preimplantation development. Together, these results establish CRISPR-RfxCas13d as a useful tool for the discovery and functional study of circRNAs at both individual and large-scale levels.

Multistep validation of a post-ERCP pancreatitis prediction system integrating multimodal data: a multicenter study.

BACKGROUND AND AIMS: The impact of various categories of information on the prediction of post-ERCP pancreatitis (PEP) remains uncertain. We comprehensively investigated the risk factors associated with PEP by constructing and validating a model incorporating multimodal data through multiple steps. METHODS: Cases (n = 1916) of ERCP were retrospectively collected from multiple centers for model construction. Through literature research, 49 electronic health record (EHR) features and 1 image feature related to PEP were identified. The EHR features were categorized into baseline, diagnosis, technique, and prevention strategies, covering pre-ERCP, intra-ERCP, and peri-ERCP phases. We first incrementally constructed models 1 to 4 incorporating these 4 feature categories and then added the image feature into models 1 to 4 and developed models 5 to 8. All models underwent testing and comparison using both internal and external test sets. Once the optimal model was selected, we conducted comparisons among multiple machine learning algorithms. RESULTS: Compared with model 2 that incorporated baseline and diagnosis features, adding technique and prevention strategies (model 4) greatly improved the sensitivity (63.89% vs 83.33%, P < .05) and specificity (75.00% vs 85.92%, P < .001). A similar tendency was observed in the internal and external tests. In model 4, the top 3 features ranked by weight were previous pancreatitis, nonsteroidal anti-inflammatory drug use, and difficult cannulation. The image-based feature has the highest weight in models 5 to 8. Finally, model 8 used a random forest algorithm and showed the best performance. CONCLUSIONS: We first developed a multimodal prediction model for identifying PEP with a clinical-acceptable performance. The image and technique features are crucial for PEP prediction.

A newly developed deep learning-based system for automatic detection and classification of small bowel lesions during double-balloon enteroscopy examination.

BACKGROUND: Double-balloon enteroscopy (DBE) is a standard method for diagnosing and treating small bowel disease. However, DBE may yield false-negative results due to oversight or inexperience. We aim to develop a computer-aided diagnostic (CAD) system for the automatic detection and classification of small bowel abnormalities in DBE. DESIGN AND METHODS: A total of 5201 images were collected from Renmin Hospital of Wuhan University to construct a detection model for localizing lesions during DBE, and 3021 images were collected to construct a classification model for classifying lesions into four classes, protruding lesion, diverticulum, erosion & ulcer and angioectasia. The performance of the two models was evaluated using 1318 normal images and 915 abnormal images and 65 videos from independent patients and then compared with that of 8 endoscopists. The standard answer was the expert consensus. RESULTS: For the image test set, the detection model achieved a sensitivity of 92% (843/915) and an area under the curve (AUC) of 0.947, and the classification model achieved an accuracy of 86%. For the video test set, the accuracy of the system was significantly better than that of the endoscopists (85% vs. 77 ± 6%, p < 0.01). For the video test set, the proposed system was superior to novices and comparable to experts. CONCLUSIONS: We established a real-time CAD system for detecting and classifying small bowel lesions in DBE with favourable performance. ENDOANGEL-DBE has the potential to help endoscopists, especially novices, in clinical practice and may reduce the miss rate of small bowel lesions.

The effect of incorporating domain knowledge with deep learning in identifying benign and malignant gastric whitish lesions: A retrospective study.

BACKGROUND AND AIM: Early whitish gastric neoplasms can be easily misdiagnosed; differential diagnosis of gastric whitish lesions remains a challenge. We aim to build a deep learning (DL) model to diagnose whitish gastric neoplasms and explore the effect of adding domain knowledge in model construction. METHODS: We collected 4558 images from two institutions to train and test models. We first developed two sole DL models (1 and 2) using supervised and semi-supervised algorithms. Then we selected diagnosis-related features through literature research and developed feature-extraction models to determine features including boundary, surface, roundness, depression, and location. Then predictions of the five feature-extraction models and sole DL model were combined and inputted into seven machine-learning (ML) based fitting-diagnosis models. The optimal model was selected as ENDOANGEL-WD (whitish-diagnosis) and compared with endoscopists. RESULTS: Sole DL 2 had higher sensitivity (83.12% vs 68.67%, Bonferroni adjusted P = 0.024) than sole DL 1. Adding domain knowledge, the decision tree performed best among the seven ML models, achieving higher specificity than DL 1 (84.38% vs 72.27%, Bonferroni adjusted P < 0.05) and higher accuracy than DL 2 (80.47%, Bonferroni adjusted P < 0.001) and was selected as ENDOANGEL-WD. ENDOANGEL-WD showed better accuracy compared with 10 endoscopists (75.70%, P < 0.001). CONCLUSIONS: We developed a novel system ENDOANGEL-WD combining domain knowledge and traditional DL to detect gastric whitish neoplasms. Adding domain knowledge improved the performance of traditional DL, which provided a novel solution for establishing diagnostic models for other rare diseases potentially.

Discovery of Sesquiterpene Lactones with Cytotoxicity from the Herb of Youngia japonica.

In the process of searching for anti-breast cancer agents, five sesquiterpene lactones (1-5), including two previously undescribed ones, yjaponica B-C (1-2), were isolated from the herb of Youngia japonica. Their structures were elucidated by spectroscopic data analyses and Marfey's method. Cytotoxic activities of all compounds against A549, U87, and 4T1 cell lines were tested using the CCK8 assay. The result showed that compound 3 possessed the highest cytotoxic activity against 4T1 cells with an IC50 value of 10.60 µM. Furthermore, compound 3 distinctly induced apoptosis, inhibited immigration, and blocked the cell cycle of 4T1 cells. In addition, compound 3 induced the production of reactive oxygen species. Further anticancer mechanism studies showed that compound 3 significantly upregulated expression of the cleaved caspase 3 and PARP, whereas it downregulated the expression of Bcl-2, cyclin D1, cyclin A2, CDK4, and CDK2. Taken together, our results demonstrate that compound 3 has a high potential of being used as a leading compound for the discovery of new anti-breast cancer agent.

Electrophysiological and morphological properties of prefrontal pyramidal neurons innervated by mediodorsal thalamus.

The high-order cognitive and executive functions are necessary for an individual to survive. The densely bidirectional innervations between the medial prefrontal cortex (mPFC) and the mediodorsal thalamus (MD) play a vital role in regulating high-order functions. Pyramidal neurons in mPFC have been classified into several subclasses according to their morphological and electrophysiological properties, but the properties of the input-specific pyramidal neurons in mPFC remain poorly understood. The present study aimed to profile the morphological and electrophysiological properties of mPFC pyramidal neurons innervated by MD. In the past, the studies for characterizing the morphological and electrophysiological properties of neurons mainly relied on the electrophysiological recording of a large number of neurons and their morphologic reconstructions. But, it is a low efficient method for characterizing the circuit-specific neurons. The present study combined the advantages of traditional morphological and electrophysiological methods with machine learning to address the shortcomings of the past method, to establish a classification model for the morphological and electrophysiological properties of mPFC pyramidal neurons, and to achieve more accurate and efficient identification of the properties from a small size sample of neurons. We labeled MD-innervated pyramidal neurons of mPFC using the trans-synaptic neural circuitry tracing method and obtained their morphological properties using whole-cell patch-clamp recording and morphologic reconstructions. The results showed that the classification model established in the present study could predict the electrophysiological properties of MD-innervated pyramidal neurons based on their morphology. MD-innervated pyramidal neurons exhibit larger basal dendritic length but lower apical dendrite complexity compared to non-MD-innervated neurons in the mPFC. The morphological characteristics of the two subtypes (ET-1 and ET-2) of mPFC pyramidal neurons innervated by MD are different, with the apical dendrites of ET-1 neurons being longer and more complex than those of ET-2 neurons. These results suggest that the electrophysiological properties of MD- innervated pyramidal neurons within mPFC correlate with their morphological properties, indicating that the different roles of these two subclasses in local circuits within PFC, as well as in PFC-cortical/subcortical brain region circuits.

Biotinylated Tn5 transposase-mediated CUT&Tag efficiently profiles transcription factor-DNA interactions in plants.

In contrast to CUT&Tag approaches for profiling bulk histone modifications, current CUT&Tag methods for analysing specific transcription factor (TF)-DNA interactions remain technically challenging due to TFs having relatively low abundance. Moreover, an efficient CUT&Tag strategy for plant TFs is not yet available. Here, we first applied biotinylated Tn5 transposase-mediated CUT&Tag (B-CUT&Tag) to produce high-quality libraries for interrogating TF-DNA interactions. B-CUT&Tag combines streptavidin-biotin-based DNA purification with routine CUT&Tag, optimizing the removal of large amounts of intact chromatin not targeted by specific TFs. The biotinylated chromatin fragments are then purified for construction of deep sequencing libraries or qPCR analysis. We applied B-CUT&Tag to probe genome-wide DNA targets of Squamosa promoter-binding-like protein 9 (SPL9), a well-established TF in Arabidopsis; the resulting profiles were efficient and consistent in demonstrating its well-established target genes in juvenile-adult transition/flowering, trichome development, flavonoid biosynthesis, wax synthesis and branching. Interestingly, our results indicate functions of AtSPL9 in modulating growth-defence trade-offs. In addition, we established a method for applying qPCR after CUT&Tag (B-CUT&Tag-qPCR) and successfully validated the binding of SPL9 in Arabidopsis and PHR2 in rice. Our study thus provides a convenient and highly efficient CUT&Tag strategy for profiling TF-chromatin interactions that is widely applicable to the annotation of cis-regulatory elements for crop improvement.

A novel mRNA rabies vaccine as a promising candidate for rabies post-exposure prophylaxis protects animals from different rabies viruses.

Rabies, caused by the rabies virus (RABV), is the most fatal zoonotic disease. It is a neglected tropical disease which remains a major public health problem, causing approximately 59,000 deaths worldwide annually. Despite the existence of effective vaccines, the high incidence of human rabies is mainly linked to tedious vaccine immunisation procedures and the overall high cost of post-exposure prophylaxis. Therefore, it is necessary to develop an effective vaccine that has a simple procedure and is affordable to prevent rabies infection in humans. RABV belongs to the genus Lyssavirus and family Rhabdoviridae. Previous phylogenetic analyses have identified seven major clades of RABV in China (China I-VII), confirmed by analysing nucleotide sequences from both the G and N proteins. This study evaluated the immunogenicity and protective capacity of SYS6008, an mRNA rabies vaccine expressing rabies virus glycoprotein, in mice and cynomolgus macaques. We demonstrated that SYS6008 induced sufficient levels of rabies neutralising antibody (RVNA) in mice. In addition, SYS6008 elicited strong and durable RVNA responses in vaccinated cynomolgus macaques. In the pre-exposure prophylaxis murine model, one or two injections of SYS6008 at 1/10 or 1/30 of dosage provided protection against a challenge with a 30-fold LD50 of rabies virus (China I and II clades). We also demonstrated that in the post-exposure prophylaxis murine model, which was exposed to lethal rabies virus (China I-VII clades) before vaccination, one or two injections of SYS6008 at both 1/10 and 1/30 dosages provided better protection against rabies virus challenge than the immunization by five injections of commercial vaccines at the same dosage. In addition, we proved that SYS6008-induced RVNAs could neutralise RABV from the China I-VII clades. Finally, 1/10 of the dosage of SYS6008 was able to stimulate significant RABV-G specificity in the T cell response. Furthermore, we found that SYS6008 induced high cellular immunity, including RABV-G-specific T cell responses and memory B cells. Our results imply that the SYS6008 rabies vaccine, with a much simpler vaccination procedure, better immunogenicity, and enhanced protective capacity, could be a candidate vaccine for post-exposure prophylaxis of rabies infections.

A deep-learning based system using multi-modal data for diagnosing gastric neoplasms in real-time (with video).

BACKGROUND: White light (WL) and weak-magnifying (WM) endoscopy are both important methods for diagnosing gastric neoplasms. This study constructed a deep-learning system named ENDOANGEL-MM (multi-modal) aimed at real-time diagnosing gastric neoplasms using WL and WM data. METHODS: WL and WM images of a same lesion were combined into image-pairs. A total of 4201 images, 7436 image-pairs, and 162 videos were used for model construction and validation. Models 1-5 including two single-modal models (WL, WM) and three multi-modal models (data fusion on task-level, feature-level, and input-level) were constructed. The models were tested on three levels including images, videos, and prospective patients. The best model was selected for constructing ENDOANGEL-MM. We compared the performance between the models and endoscopists and conducted a diagnostic study to explore the ENDOANGEL-MM's assistance ability. RESULTS: Model 4 (ENDOANGEL-MM) showed the best performance among five models. Model 2 performed better in single-modal models. The accuracy of ENDOANGEL-MM was higher than that of Model 2 in still images, real-time videos, and prospective patients. (86.54 vs 78.85%, P = 0.134; 90.00 vs 85.00%, P = 0.179; 93.55 vs 70.97%, P < 0.001). Model 2 and ENDOANGEL-MM outperformed endoscopists on WM data (85.00 vs 71.67%, P = 0.002) and multi-modal data (90.00 vs 76.17%, P = 0.002), significantly. With the assistance of ENDOANGEL-MM, the accuracy of non-experts improved significantly (85.75 vs 70.75%, P = 0.020), and performed no significant difference from experts (85.75 vs 89.00%, P = 0.159). CONCLUSIONS: The multi-modal model constructed by feature-level fusion showed the best performance. ENDOANGEL-MM identified gastric neoplasms with good accuracy and has a potential role in real-clinic.

Cryo-EM structure of the open high-conductance Ca2+-activated K+ channel.

The Ca2+-activated K+ channel, Slo1, has an unusually large conductance and contains a voltage sensor and multiple chemical sensors. Dual activation by membrane voltage and Ca2+ renders Slo1 central to processes that couple electrical signalling to Ca2+-mediated events such as muscle contraction and neuronal excitability. Here we present the cryo-electron microscopy structure of a full-length Slo1 channel from Aplysia californica in the presence of Ca2+ and Mg2+ at a resolution of 3.5 Å. The channel adopts an open conformation. Its voltage-sensor domain adopts a non-domain-swapped attachment to the pore and contacts the cytoplasmic Ca2+-binding domain from a neighbouring subunit. Unique structural features of the Slo1 voltage sensor suggest that it undergoes different conformational changes than other known voltage sensors. The structure reveals the molecular details of three distinct divalent cation-binding sites identified through electrophysiological studies of mutant Slo1 channels.

Structural basis for gating the high-conductance Ca2+-activated K+ channel.

The precise control of an ion channel gate by environmental stimuli is crucial for the fulfilment of its biological role. The gate in Slo1 K+ channels is regulated by two separate stimuli, intracellular Ca2+ concentration and membrane voltage. Slo1 is thus central to understanding the relationship between intracellular Ca2+ and membrane excitability. Here we present the Slo1 structure from Aplysia californica in the absence of Ca2+ and compare it with the Ca2+-bound channel. We show that Ca2+ binding at two unique binding sites per subunit stabilizes an expanded conformation of the Ca2+ sensor gating ring. These conformational changes are propagated from the gating ring to the pore through covalent linkers and through protein interfaces formed between the gating ring and the voltage sensors. The gating ring and the voltage sensors are directly connected through these interfaces, which allow membrane voltage to regulate gating of the pore by influencing the Ca2+ sensors.

MANF ameliorates DSS-induced mouse colitis via restricting Ly6ChiCX3CR1int macrophage transformation and suppressing CHOP-BATF2 signaling pathway.

Mesencephalic astrocyte-derived neurotrophic factor (MANF), an endoplasmic reticulum stress-inducible secreting protein, has evolutionarily conserved immune-regulatory function that contributes to the negative regulation of inflammation in macrophages. In this study, we investigated the profiles of MANF in the macrophages of the patients with active inflammatory bowel disease (IBD) and the mice with experimental colitis, which was induced in both myeloid cell-specific MANF knockout mice and wild-type mice by 3% dextran sodium sulfate (DSS) for 7 days. We found that MANF expression was significantly increased in intestinal macrophages from both the mice with experimental colitis and patients with active IBD. DSS-induced colitis was exacerbated in myeloid cell-specific MANF knockout mice. Injection of recombinant human MANF (rhMANF, 10 mg·kg-1·d-1, i.v.) from D4 to D6 significantly ameliorated experimental colitis in DSS-treated mice. More importantly, MANF deficiency in myeloid cells resulted in a dramatic increase in the number of Ly6ChiCX3CRint proinflammatory macrophages in colon lamina propria of DSS-treated mice, and the proinflammatory cytokines and chemokines were upregulated as well. Meanwhile, we demonstrated that MANF attenuated Th17-mediated immunopathology by inhibiting BATF2-mediated innate immune response and downregulating CXCL9, CXCL10, CXCL11 and IL-12p40; MANF functioned as a negative regulator in inflammatory macrophages via inhibiting CHOP-BATF2 signaling pathway, thereby protecting against DSS-induced mouse colitis. These results suggest that MANF ameliorates colon injury by negatively regulating inflammatory macrophage transformation, which shed light on a potential therapeutic target for IBD.

The value of ultrasensitive C-reactive protein and homocysteine levels in predicting the diagnosis and functional prognostic assessment of cerebral infarction in the elderly.

OBJECTIVE: To evaluate the diagnostic value of ultrasensitive C-reactive protein (hs-CRP) and homocysteine (Hcy) for cerebral infarction. METHODS: 260 elderly patients with cerebral infarction were recruited and assigned to the stroke group, and 60 healthy elderly were identified as controls and included in the normal group. Serum samples of all subjects were collected at the time of admission for the determination of hs-CRP and Hcy levels. RESULTS: Patients with cerebral infarction exhibited significantly higher hs-CRP and Hcy levels than healthy controls. the patients were then categorized into mild-moderate and moderate-severe groups according to the National Institutes of Health Stroke Scale (NIHSS) score. No significant association was identified between Hcy levels and infarction severity, while more severe infarction was potentially related to higher hs-CRP levels, as evidenced by the higher hs-CRP levels observed in patients with moderate-severe infarction versus a milder severity. Patients with disease recurrence within 2 years were also included in a recurrence group, while those without recurrence were in a non-recurrence group. Results showed that patients with or without disease recurrence had similar hs-CRP and Hcy levels. CONCLUSION: In elderly patients with cerebral infarction, serum hs-CRP, and Hcy levels are potentially promising markers for the diagnosis of stroke, assessment of stroke severity, and prediction of functional recovery. hs-CRP provides more benefits in diagnosing cerebral infarction, and Hcy is more conducive to the assessment of stroke severity and prediction of functional recovery. Combined detection of the two indices did not offer additional benefits in diagnostic and predictive efficacy.

High-performance full-color imaging system based on end-to-end joint optimization of computer-generated holography and metalens.

Metasurface has drawn extensive attention due to its capability of modulating light with a high degree of freedom through ultrathin and sub-wavelength optical elements, and metalens, as one of its important applications, promises to replace the bulky refractive optics, facilitating the imaging system light-weight and compact characteristics. Besides, computer-generated holography (CGH) is of substantial interest for three-dimensional (3D) imaging technology by virtue of its ability of restoring the whole optical wave field and re-constructing the true 3D scene. Consequently, the combination of metalens and CGH holds transformative potential in enabling the miniaturization of 3D imaging systems. However, its imaging performance is subject to the aberrations and speckle noises originating from the metalens and CGH. Inspired by recent progress that computational imaging can be applied to close the gap, a novel full-color imaging system, adopting end-to-end joint optimization of metalens and CGH for high imaging quality, is proposed in this paper. The U-net based network as the pre-processing adjusts weights to make the holographic reconstruction offset imaging defects, incorporating the imaging processing into the step of generating hologram. Optimized by deep learning, the proposed imaging system is capable of full-color imaging with high fidelity in a compact form factor, envisioned to take an essential step towards the high-performance miniaturized imaging system.

Shortwave infrared single-pixel spectral imaging based on a GSST phase-change metasurface.

Shortwave infrared (SWIR) spectral imaging obtains spectral fingerprints corresponding to overtones of molecular vibrations invisible to conventional silicon-based imagers. However, SWIR imaging is challenged by the excessive cost of detectors. Single-pixel imaging based on compressive sensing can alleviate the problem but meanwhile presents new difficulties in spectral modulations, which are prerequisite in compressive sampling. In this work, we theoretically propose a SWIR single-pixel spectral imaging system with spectral modulations based on a Ge2Sb2Se4Te1 (GSST) phase-change metasurface. The transmittance spectra of the phase-change metasurface are tuned through wavelength shifts of multipole resonances by varying crystallinities of GSST, validated by the multipole decompositions and electromagnetic field distributions. The spectral modulations constituted by the transmittance spectra corresponding to the 11 phases of GSST are sufficient for the compressive sampling on the spectral domain of SWIR hyperspectral images, indicated by the reconstruction in false color and point spectra. Moreover, the feasibility of optimization on phase-change metasurface via coherence minimization is demonstrated through the designing of the GSST pillar height. The concept of spectral modulation with phase-change metasurface overcomes the static limitation in conventional modulators, whose integratable and reconfigurable features may pave the way for high-efficient, low-cost, and miniaturized computational imaging based on nanophotonics.

Residual image recovery method based on the dual-camera design of a compressive hyperspectral imaging system.

Compressive hyperspectral imaging technology can quickly detect the encoded two-dimensional measurements and reconstruct the three-dimensional hyperspectral images offline, which is of great significance for object detection and analysis. To provide more information for reconstruction and improve the reconstruction quality, some of the latest compressive hyperspectral imaging systems adopt a dual-camera design. To utilize the information from additional camera more efficiently, this paper proposes a residual image recovery method. The proposed method takes advantage of the structural similarity between the image captured by the additional camera and the hyperspectral image, combining the measurements from the additional camera and coded aperture snapshot spectral imaging (CASSI) sensor to construct an estimated hyperspectral image. Then, the component of the estimated hyperspectral image is subtracted from the measurement of the CASSI sensor to obtain the residual data. The residual data is used to reconstruct the residual hyperspectral image. Finally, the reconstructed hyperspectral image is the sum of the estimated and residual image. Compared with some state-of-the-art algorithms based on such systems, the proposed method can significantly improve the reconstruction quality of hyperspectral image.