The critical role of P2XR/PGC-1α signalling pathway in hypoxia-mediated pyroptosis and M1/M2 phenotypic differentiation of mouse microglia.

Microglia are endogenous immune cells in the brain, and their pyroptosis and phenotype dichotomy are proved to play roles in neurodegenerative diseases. We investigated whether and how hypoxia affected pyroptosis and phenotype polarization in mouse microglia. Primary mouse microglia and BV2 microglia were exposed to hypoxia. Pyroptosis and M1/M2 phenotype were assessed by measuring gasdermin D truncation and M1/M2 surface marker expression. Mechanisms including purinergic ionotropic receptor (P2XR), peroxisome proliferator-activated receptor coactivator-1α (PGC-1α) and NOD-like receptor protein 3 (NLRP3) inflammasome were investigated. We reported hypoxia (90% N2, 5% O2 and 5% CO2) induced pyroptosis and promoted M1 phenotype polarization in primary mouse microglia and BV2 microglia, and the effect appeared after 6 h exposure. Although hypoxia (90% N2, 5% O2 and 5% CO2, 6 h) had no effect on P2X1R and P2X7R expression, it increased P2X4R expression and decreased PGC-1α expression. Interestingly, blockade of P2X4R or P2X7R abolished hypoxia-modulated PGC-1α expression, pyroptosis and M1 polarization. PGC-1α overexpression or overactivation alleviated hypoxia-induced pyroptosis and M1 polarization, while PGC-1α knockdown or deactivation promoted pyroptosis and M1 polarization under normoxic situation. Further, hypoxia induced NLRP3 expression and activated caspase-1 and induced the phosphorylation of NF-κB and reduced the phosphorylation of STAT3/6. NLRP3 inhibitor and caspase-1 inhibitor abolished hypoxia-induced pyroptosis, while NF-κB inhibitor and STAT phosphorylation inducer ameliorated hypoxia-induced M1 polarization. In addition, NF-κB activator and STAT3/6 inhibitor caused microglia M1 polarization under normoxic situation. We concluded in cultured mouse microglia, hypoxia may induce pyroptosis via P2XR/PGC-1α/NLRP3/caspase-1 pathway and trigger M1 polarization through P2XR/PGC-1α/NF-κB/STAT3/6 pathway.

Immune responses and protective efficacy of American eel (Anguilla rostrata) immunized with a formalin-inactivated vaccine against Anguillid herpesvirus.

Anguillid herpesvirus 1 (AngHV), the causative agent of "mucus sloughing and hemorrhagic septicemia disease", causes serious infectious diseases in farmed eel. Among the effective prevention and control strategies, vaccination is one of the most effective approaches. However, no vaccine for AngHV is available. Our study developed a formalin-inactivated AngHV vaccine and evaluated its performance in American eels. Initially, AngHV-FJ, a strain of AngHV, was inactivated completely by 0.1 % formaldehyde, mixed with adjuvant Montanide ISA 763 A VG (763A). Then, vaccines containing different amount of antigen (3 × 106 PFU, 3 × 105 PFU, 3 × 104 PFU, 3 × 103 PFU) were immunized in each American eels. The results showed that the 3 × 105 PFU/fish was the proper dose. The inactivated AngHV vaccine was proven safe for American eels by back intramuscular injection. The results of twice immunization showed that antibody production peaked in the 8th week after the first immunization, and the antibody titer was 1:64,000. Furthermore, the immunized fishes challenged with AngHV (105 PFU/ml immersion) showed a significantly lower incidence rate (33.33 %) than the control group (95.65 %). The survival of the fish in the vaccine group (94.44 %) was significantly higher than the control group (60.87 %). The relative survival rate of the vaccinated group was 85.80 %. Also, vaccine group tissue collected at 7th d post-challenge showed reduced tissue damage and a lower virus load than the control group. The expression of cytokines of IL-1ß, IFN-α, IFN-γ, Mx1, RIG-1, and IRF-3, were significantly lower in the vaccine group than the control group at the 7th and 14th d post-challenge. Overall, the formalin-inactivated AngHV vaccine was safe and had immune protective effects against AngHV infection.

Histological Comparison of Nanofat and Lipoconcentrate: Enhanced Effects of Lipoconcentrate on Adipogenesis and Angiogenesis.

BACKGROUND: Nanofat and lipoconcentrate contain adipose-derived stem cells and growth factors, and have wide clinical applications in the regenerative field. This study aimed to investigate the microenvironmental changes associated with nanofat and lipoconcentrate. METHODS: Conventional fat, nanofat, or lipoconcentrate (0.2 mL each, n = 5 per group) were injected subcutaneously into the dorsal flanks of athymic nude mice. The graft weights were measured at postoperative week 4; the grafts and their overlying skin were used for histological analyses. RESULTS: Weights of the lipoconcentrate grafts were significantly greater than those of the conventional fat (p < 0.05) and nanofat (p < 0.01) grafts. There was no significant difference in inflammation, oil cysts, and fibrosis between the conventional fat and nanofat groups. Histological examination of the lipoconcentrate grafts showed less macrophage infiltration and the formation of fibrosis and oil cysts. Additionally, adipogenesis and angiogenesis were induced more in the lipoconcentrate grafts than in the nanofat grafts (p < 0.01). Lipoconcentrate and nanofat improved dermal thickness (p < 0.001 and p < 0.01, respectively, versus the baseline). CONCLUSION: Lipoconcentrate grafts had greater volume and shape retention than conventional fat and nanofat grafts. They had better histological structure and acted as scaffolds for adipogenesis and angiogenesis. Both products showed regenerative effects on dermal thickness; however, only lipoconcentrate grafts had the required volume and regenerative effects, allowing it to serve as a novel adipose-free grafting method for facial rejuvenation and contouring. NO LEVEL ASSIGNED: This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to Table of Contents or the online Instructions to Authors www.springer.com/00266 .

[Disease spectrum and pathogenic genes of inherited metabolic disorder in Gansu Province of China]. / ç”˜è‚ƒåœ°åŒºé—ä¼ ä»£è°¢ç— ç–¾ç— è°±åŠè‡´ç— åŸºå› åˆ†æž.

OBJECTIVES: To investigate the disease spectrum and pathogenic genes of inherited metabolic disorder (IMD) among neonates in Gansu Province of China. METHODS: A retrospective analysis was conducted on the tandem mass spectrometry data of 286 682 neonates who received IMD screening in Gansu Provincial Maternal and Child Health Hospital from January 2018 to December 2021. A genetic analysis was conducted on the neonates with positive results in tandem mass spectrometry during primary screening and reexamination. RESULTS: A total of 23 types of IMD caused by 28 pathogenic genes were found in the 286 682 neonates, and the overall prevalence rate of IMD was 0.63 (1/1 593), among which phenylketonuria showed the highest prevalence rate of 0.32 (1/3 083), followed by methylmalonic acidemia (0.11, 1/8 959) and tetrahydrobiopterin deficiency (0.06, 1/15 927). In this study, 166 variants were identified in the 28 pathogenic genes, with 13 novel variants found in 9 genes. According to American College of Medical Genetics and Genomics guidelines, 5 novel variants were classified as pathogenic variants, 7 were classified as likely pathogenic variants, and 1 was classified as the variant of uncertain significance. CONCLUSIONS: This study enriches the database of pathogenic gene variants for IMD and provides basic data for establishing an accurate screening and diagnosis system for IMD in this region.

Fecal Signatures of Streptococcus anginosus and Streptococcus constellatus for Noninvasive Screening and Early Warning of Gastric Cancer.

BACKGROUND & AIMS: Most patients with gastric cancer (GCa) are diagnosed at an advanced stage. We aimed to investigate novel fecal signatures for clinical application in early diagnosis of GCa. METHODS: This was an observational study that included 1043 patients from 10 hospitals in China. In the discovery cohort, 16S ribosomal RNA gene analysis was performed in paired samples (tissues and feces) from patients with GCa and chronic gastritis (ChG) to determine differential abundant microbes. Their relative abundances were detected using quantitative real-time polymerase chain reaction to test them as bacterial candidates in the training cohort. Their diagnostic efficacy was validated in the validation cohort. RESULTS: Significant enrichments of Streptococcus anginosus (Sa) and Streptococcus constellatus (Sc) in GCa tumor tissues (P < .05) and feces (P < .0001) were observed in patients with intraepithelial neoplasia, early and advanced GCa. Either the signature parallel test Sa∪Sc or single signature Sa/Sc demonstrated superior sensitivity (Sa: 75.6% vs 72.1%, P < .05; Sc: 84.4% vs 64.0%, P < .001; and Sa∪Sc: 91.1% vs 81.4%, P < .01) in detecting early GCa compared with advanced GCa (specificity: Sa: 84.0% vs 83.9%, Sc: 70.4% vs 82.3%, and Sa∪Sc: 64.0% vs 73.4%). Fecal signature Sa∪Sc outperformed Sa∪CEA/Sc∪CEA in the discrimination of advanced GCa (sensitivity: 81.4% vs 74.2% and 81.4% vs 72.3%, P < .01; specificity: 73.4% vs 81.0 % and 73.4% vs 81.0%). The performance of Sa∪Sc in the diagnosis of both early and advanced GCa was verified in the validation cohort. CONCLUSION: Fecal Sa and Sc are noninvasive, accurate, and sensitive signatures for early warning in GCa. (ClinicalTrials.gov, Number: NCT04638959).

GraphLoc: a graph neural network model for predicting protein subcellular localization from immunohistochemistry images.

MOTIVATION: Recognition of protein subcellular distribution patterns and identification of location biomarker proteins in cancer tissues are important for understanding protein functions and related diseases. Immunohistochemical (IHC) images enable visualizing the distribution of proteins at the tissue level, providing an important resource for the protein localization studies. In the past decades, several image-based protein subcellular location prediction methods have been developed, but the prediction accuracies still have much space to improve due to the complexity of protein patterns resulting from multi-label proteins and the variation of location patterns across cell types or states. RESULTS: Here, we propose a multi-label multi-instance model based on deep graph convolutional neural networks, GraphLoc, to recognize protein subcellular location patterns. GraphLoc builds a graph of multiple IHC images for one protein, learns protein-level representations by graph convolutions and predicts multi-label information by a dynamic threshold method. Our results show that GraphLoc is a promising model for image-based protein subcellular location prediction with model interpretability. Furthermore, we apply GraphLoc to the identification of candidate location biomarkers and potential members for protein networks. A large portion of the predicted results have supporting evidence from the existing literatures and the new candidates also provide guidance for further experimental screening. AVAILABILITY AND IMPLEMENTATION: The dataset and code are available at: www.csbio.sjtu.edu.cn/bioinf/GraphLoc. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Classification of quantum correlation using deep learning.

Quantum correlation, as an intrinsic property of quantum mechanics, has been widely employed to test the fundamental physical principles and explore the quantum-enhanced technologies. However, such correlation would be drowned and even destroyed in the conditions of high levels of loss and noise, which drops into the classical realm and renders quantum advantage ineffective. Especially in low light conditions, conventional linear classifiers are unable to extract and distinguish quantum and classical correlations with high accuracy. Here we experimentally demonstrate the classification of quantum correlation using deep learning to meet the challenge in the quantum imaging scheme. We design the convolutional neural network to learn and classify the correlated photons efficiently with only 0.1 signal photons per pixel. We show that decreasing signal intensity further weakens the correlation and makes an accurate linear classification impossible, while the deep learning method has a strong robustness of such task with the accuracy of 99.99%. These results open up a new perspective to optimize the quantum correlation in low light conditions, representing a step towards diverse applications in quantum-enhanced measurement scenarios, such as super-resolution microscope, quantum illumination, etc.

Experimental 61-partite entanglement on a three-dimensional photonic chip.

Multipartite entanglements are essential resources for proceeding tasks in quantum information science and technology. However, generating and verifying them present significant challenges, such as the stringent requirements for manipulations and the need for a huge number of building-blocks as the systems scale up. Here, we propose and experimentally demonstrate the heralded multipartite entanglements on a three-dimensional photonic chip. Integrated photonics provide a physically scalable way to achieve an extensive and adjustable architecture. Through sophisticated Hamiltonian engineering, we are able to control the coherent evolution of shared single photon in the multiple spatial modes, dynamically tuning the induced high-order W-states of different orders in a single photonic chip. Using an effective witness, we successfully observe and verify 61-partite quantum entanglements in a 121-site photonic lattice. Our results, together with the single-site-addressable platform, offer new insights into the accessible size of quantum entanglements and may facilitate the developments of large-scale quantum information processing applications.

Experimental Boson Sampling Enabling Cryptographic One-Way Function.

Boson sampling is a computational problem, which is commonly believed to be a representative paradigm for attaining the milestone of quantum advantage. So far, massive efforts have been made to the experimental large-scale boson sampling for demonstrating this milestone, while further applications of the machines remain a largely unexplored area. Here, we investigate experimentally the efficiency and security of a cryptographic one-way function that relies on coarse-grained boson sampling, in the framework of a photonic boson-sampling machine fabricated by a femtosecond laser direct writing technique. Our findings demonstrate that the implementation of the function requires moderate sample sizes, which can be over 4 orders of magnitude smaller than the ones predicted by the Chernoff bound; whereas for numbers of photons n≥3 and bins d∼poly(m,n), the same output of the function cannot be generated by nonboson samplers. Our Letter is the first experimental study that deals with the potential applications of boson sampling in the field of cryptography and paves the way toward additional studies in this direction.

Noninvasive predictive models based on lifestyle analysis and risk factors for early-onset colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) incidence has increased among patients aged <50 years. Exploring high-risk factors and screening high-risk populations may help lower early-onset CRC (EO-CRC) incidence. We developed noninvasive predictive models for EO-CRC and investigated its risk factors. METHODS: This retrospective multicenter study collected information on 1756 patients (811 patients with EO-CRC and 945 healthy controls) from two medical centers in China. Sociodemographic features, clinical symptoms, medical and family history, lifestyle, and dietary factors were measured. Patients from one cohort were randomly assigned (8:2) to two groups for model establishment and internal validation, and another independent cohort was used for external validation. Multivariable logistic regression, random forest, and eXtreme Gradient Boosting (XGBoost) were performed to establish noninvasive predictive models for EO-CRC. Some variables in the model influenced EO-CRC occurrence and were further analyzed. Multivariable logistic regression analysis yielded adjusted odd ratios (ORs) and 95% confidence intervals (CIs). RESULTS: All three models showed good performance, with areas under the receiver operator characteristic curves (AUCs) of 0.82, 0.84, and 0.82 in the internal and 0.78, 0.79, and 0.78 in the external validation cohorts, respectively. Consumption of sweet (OR 2.70, 95% CI 1.89-3.86, P < 0.001) and fried (OR 2.16, 95% CI 1.29-3.62, P < 0.001) foods ≥3 times per week was significantly associated with EO-CRC occurrence. CONCLUSION: We established noninvasive predictive models for EO-CRC and identified multiple nongenetic risk factors, especially sweet and fried foods. The model has good performance and can help predict the occurrence of EO-CRC in the Chinese population.

Impacts of high-quality coal mine drainage recycling for replenishment of aquatic ecosystems in arid regions of China: Bacterial community responses.

Coal mine water is usually recycled as supplementary water for aquatic ecosystems in arid and semiarid mining regions of China. To ensure ecosystem health, the coal mine water is rigorously treated using several processes, including reverse osmosis, to meet surface water quality standards. However, the potential environmental impacts of this management pattern on the ecological function of receiving water bodies are unclear. In this study, we built several microcosm water ecosystems to simulate the receiving water bodies. High-quality treated coal mine drainage was mixed into the model water bodies at different concentrations, and the sediment bacterial community response and functional changes were systematically investigated. The results showed that the high-quality coal mine drainage could still shape bacterial taxonomic diversity, community composition and structure, with a concentration threshold of approximately 50%. Moreover, both the Mantel test and the structural equation model indicated that the salinity fluctuation caused by the receiving of coal mine drainage was the primary factor shaping the bacterial communities. 10 core taxa in the molecular ecological network influenced by coal mine drainage were identified, with the most critical taxa being patescibacteria and g_Geothermobacter. Furthermore, the pathway of carbohydrate metabolism as well as signaling molecules and interactions was up-regulated, whereas amino acid metabolism showed the opposite trend. All results suggested that the complex physical-chemical and biochemical processes in water ecosystems may be affected by the coal mine drainage. The bacterial community response and underlying functional changes may accelerate internal nutrient cycling, which may have a potential impact on algal bloom outbreaks.

Cocultivation of pigeon pea hairy root cultures and Aspergillus for the enhanced production of cajaninstilbene acid.

Pigeon pea hairy root cultures (PPHRCs) have been proven to be a promising alternative for the production of health-beneficial phenolic compounds, such as the most important health-promoting compound, i.e., cajaninstilbene acid (CSA). In this study, PPHRCs were cocultured with live Aspergillus fungi for further improving phenolic productivity via biological elicitation. Aspergillus oryzae CGMCC 3.951 (AO 3.951) was found to be the optimal fungus that could achieve the maximum increment of CSA (10.73-fold increase) in 42-day-old PPHRCs under the inoculum size of mycelia 0.50% and cocultivation time 36 h. More precisely, the contents of CSA in hairy roots and culture media after fungal elicitation increased by 9.87- and 62.18-fold over control, respectively. Meanwhile, the contents of flavonoid glycosides decreased, while aglycone yields increased upon AO 3.951 elicitation. Moreover, AO 3.951 could trigger the oxidative stress and pathogen defense response thus activating the expression of biosynthesis- and ABC transporter-related genes, which contributed to the intracellular accumulation and extracellular secretion of phenolic compounds (especially CSA) in PPHRCs. And PAL2, 4CL2, STS1, and I3'H were likely to be the potential key enzyme genes regulating the biosynthesis of CSA, and ABCB11X1-1, ABCB11, and ABCG24X2 were closely related to the transmembrane transport of CSA. Overall, the cocultivation approach could make PPHRCs more commercially attractive for the production of high-value phenolic compounds such as CSA and flavonoid aglycones in nutraceutical/medicinal fields. And the elucidation of crucial biosynthesis and transport genes was important for systematic metabolic engineering aimed at increasing CSA productivity. KEY POINTS: • Cocultivation of PPHRCs and live fungi was to enhance CSA production and secretion. • PPHRCs augmented CSA productivity 10.73-fold when cocultured with AO 3.951 mycelia. • Several biosynthesis and transport genes related to CSA production were clarified.

Oncologic Safety and Efficacy of Cell-Assisted Lipotransfer for Breast Reconstruction in a Murine Model of Residual Breast Cancer.

BACKGROUND: Cell-assisted lipotransfer (CAL) is a novel technique for fat grafting that combines the grafting of autologous fat and adipose-derived stromal cells (ASCs) to enhance fat graft retention; however, its oncologic safety is controversial. METHODS: Herein, we investigated the oncologic safety of CAL for breast reconstruction using a murine model of residual breast cancer. Various concentrations of 4T1 cells (murine breast cancer cells) were injected into female mastectomized BALB/c mice to determine the appropriate concentration for injection. One week after injection, mice were divided into control (100 µL fat), low CAL (2.5 × 105 ASCs/100 µL fat), and high CAL (1.0 × 106 ASCs/100 µL fat) groups, and fat grafting was performed. The injection of 5.0 × 103 4T1 cells was appropriate to produce a murine model of residual breast cancer. RESULTS: The weight of the fat tumor mass was significantly higher in the high CAL group than in the other groups (p < 0.05). However, the estimated tumor weight was not significantly different between the groups. Additionally, the fat graft survival rate was significantly higher in the high CAL group than in the control and low CAL groups (p < 0.05). No significant difference was noted in the percentage of Ki-67-positive cells, suggesting that tumor proliferation was not significantly different between the groups. CONCLUSION: In summary, CAL significantly improved fat graft survival without affecting tumor size and proliferation in a murine model of residual breast cancer. These results highlight the oncologic safety of CAL for breast reconstruction. NO LEVEL ASSIGNED: This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Evaluation of housekeeping genes as references for quantitative real-time PCR analysis of European eel, Anguilla anguilla.

Eels are important aquaculture species for which an increasing number of reference genes are being identified and applied. In this study, five housekeeping genes [RPL7 (ribosomal protein L7), 18 S (18 S ribosomal RNA), EF1A (elongation factor 1α), ACTB (ß-actin) and GAPDH (glyceraldehyde-3-phosphate dehydrogenase)] were chosen to evaluate their reliability as reference genes for quantitative real-time PCR (qPCR) for the study of Anguilla anguilla. The expression of the selected genes in different eel tissues was determined using qPCR at different growth stages or upon challenge by Anguillid herpesvirus (AngHV), and the expression levels of these genes were then compared and evaluated using the geNorm and NormFinder algorithms. Then, RefFinder was used to comprehensively rank the examined housekeeping genes. Interestingly, the expression of the evaluated housekeeping genes exhibited tissue-dependent and treatment-dependent variations. In different growth periods A. anguilla tissues, the most stable genes were the following: ACTB in mucus; 18 S in skin and kidney; RPL7 in muscle, gill, intestine and brain; EF1A in heart and liver; and GAPDH in spleen. In contrast, in AngHV-challenged A. anguilla tissues, the most stable genes were the following: 18 S in mucus; RPL7 in skin, gill, heart, spleen, kidney and intestine; EF1A in muscle and liver; and ACTB in brain. Further comparison analysis indicated that the expression of RPL7 and EF1A was stable in multiple A. anguilla tissues in different growth periods and in eels challenged by AngHV. Nonetheless, the expression level of GAPDH in eel tissues was lower, and it was unstable in several tissues. These results indicated that the selection of reference genes for qPCR analysis in A. anguilla should be made in accordance with experimental parameters, and both RPL7 and EF1A could be used as reference genes for qPCR study of A. anguilla at different growth stages or upon challenge by AngHV. The reference genes identified in this study could improve the accuracy of qPCR data and facilitate further studies aimed at understanding the biology of eels.

Incorporating label correlations into deep neural networks to classify protein subcellular location patterns in immunohistochemistry images.

Analysis of protein subcellular localization is a critical part of proteomics. In recent years, as both the number and quality of microscopic images are increasing rapidly, many automated methods, especially convolutional neural networks (CNN), have been developed to predict protein subcellular location(s) based on bioimages, but their performance always suffers from some inherent properties of the problem. First, many microscopic images have non-informative or noisy sections, like unstained stroma and unspecific background, which affect the extraction of protein expression information. Second, the patterns of protein subcellular localization are very complex, as a lot of proteins locate in more than one compartment. In this study, we propose a new label-correlation enhanced deep neural network, laceDNN, to classify the subcellular locations of multi-label proteins from immunohistochemistry images. The model uses small representative patches as input to alleviate the image noise issue, and its backbone is a hybrid architecture of CNN and recurrent neural network, where the former network extracts representative image features and the latter learns the organelle dependency relationships. Our experimental results indicate that the proposed model can improve the performance of multi-label protein subcellular classification.

Genomic Architecture of Rapid Parallel Adaptation to Fresh Water in a Wild Fish.

Rapid adaptation to novel environments may drive changes in genomic regions through natural selection. However, the genetic architecture underlying these adaptive changes is still poorly understood. Using population genomic approaches, we investigated the genomic architecture that underlies rapid parallel adaptation of Coilia nasus to fresh water by comparing four freshwater-resident populations with their ancestral anadromous population. Linkage disequilibrium network analysis and population genetic analyses revealed two putative large chromosome inversions on LG6 and LG22, which were enriched for outlier loci and exhibited parallel association with freshwater adaptation. Drastic frequency shifts and elevated genetic differentiation were observed for the two chromosome inversions among populations, suggesting that both inversions would undergo divergent selection between anadromous and resident ecotypes. Enrichment analysis of genes within chromosome inversions showed significant enrichment of genes involved in metabolic process, immunoregulation, growth, maturation, osmoregulation, and so forth, which probably underlay differences in morphology, physiology and behavior between the anadromous and freshwater-resident forms. The availability of beneficial standing genetic variation, large optimum shift between marine and freshwater habitats, and high efficiency of selection with large population size could lead to the observed rapid parallel adaptive genomic change. We propose that chromosomal inversions might have played an important role during the evolution of rapid parallel ecological divergence in the face of environmental heterogeneity in C. nasus. Our study provides insights into the genomic basis of rapid adaptation of complex traits in novel habitats and highlights the importance of structural genomic variants in analyses of ecological adaptation.

Reducing circuit complexity in optical quantum computation using 3D architectures.

Integrated photonic architectures based on optical waveguides are one of the leading candidates for the future realisation of large-scale quantum computation. One of the central challenges in realising this goal is simultaneously minimising loss whilst maximising interferometric visibility within waveguide circuits. One approach is to reduce circuit complexity and depth. A major constraint in most planar waveguide systems is that beamsplitter transformations between distant optical modes require numerous intermediate SWAP operations to couple them into nearest neighbour proximity, each of which introduces loss and scattering. Here, we propose a 3D architecture which can significantly mitigate this problem by geometrically bypassing trivial intermediate operations. We demonstrate the viability of this concept by considering a worst-case 2D scenario, where we interfere the two most distant optical modes in a planar structure. Using femtosecond laser direct-writing technology we experimentally construct a 2D architecture to implement Hong-Ou-Mandel interference between its most distant modes, and a 3D one with corresponding physical dimensions, demonstrating significant improvement in both fidelity and efficiency in the latter case. In addition to improving fidelity and efficiency of individual non-adjacent beamsplitter operations, this approach provides an avenue for reducing the optical depth of circuits comprising complex arrays of beamsplitter operations.

Generating Haar-Uniform Randomness Using Stochastic Quantum Walks on a Photonic Chip.

As random operations for quantum systems are intensively used in various quantum information tasks, a trustworthy measure of the randomness in quantum operations is highly demanded. The Haar measure of randomness is a useful tool with wide applications, such as boson sampling. Recently, a theoretical protocol was proposed to combine quantum control theory and driven stochastic quantum walks to generate Haar-uniform random operations. This opens up a promising route to converting classical randomness to quantum randomness. Here, we implement a two-dimensional stochastic quantum walk on the integrated photonic chip and demonstrate that the average of all distribution profiles converges to the even distribution when the evolution length increases, suggesting the 1-pad Haar-uniform randomness. We further show that our two-dimensional array outperforms the one-dimensional array of the same number of waveguide for the speed of convergence. Our Letter demonstrates a scalable and robust way to generate Haar-uniform randomness that can provide useful building blocks to boost future quantum information techniques.

Direct Observation of Dynamically Localized Quantum Optical States.

Quantum-correlated biphoton states play an important role in quantum communication and processing, especially considering the recent advances in integrated photonics. However, it remains a challenge to flexibly transport quantum states on a chip, when dealing with large-scale sophisticated photonic designs. The equivalence between certain aspects of quantum optics and solid-state physics makes it possible to utilize a range of powerful approaches in photonics, including topologically protected boundary states, graphene edge states, and dynamic localization. Optical dynamic localization allows efficient protection of classical signals in photonic systems by implementing an analogue of an external alternating electric field. Here, we report on the observation of dynamic localization for quantum-correlated biphotons, including both the generation and the propagation aspects. As a platform, we use sinusoidal waveguide arrays with cubic nonlinearity. We record biphoton coincidence count rates as evidence of robust generation of biphotons and demonstrate the dynamic localization features in both spatial and temporal space by analyzing the quantum correlation of biphotons at the output of the waveguide array. Experimental results demonstrate that various dynamic modulation parameters are effective in protecting quantum states without introducing complex topologies. Our Letter opens new avenues for studying complex physical processes using photonic chips and provides an alternative mechanism of protecting communication channels and nonclassical quantum sources in large-scale integrated quantum optics.

Improved electrochemical properties of polypyrrole with cucurbit[6]uril via supramolecular interactions.

A supramolecular polymer was developed through the encapsulation of polypyrrole by cucurbit[6]uril (PPy@Q[6]), which was employed as the electrode material to improve the capacitor ability of conductive polypyrrole. In the optimized ratio of 2 : 1 (CPPy : CQ[6]), the capacitor properties of the supramolecular material were evaluated, and a high specific capacitance of 414 F g-1 at 10 mV s-1 was obtained, which was 3.1 times higher than that of pure polypyrrole (132 F g-1). A comprehensive analysis suggested that the capacitance performances should be relevant to the component, surface area, and pore volume of the materials. The addition of 0.4 M Fe2(SO4)3 into the electrolyte provided a surprising specific capacitance of 3530 F g-1 on the cucurbituril-encapsulated polypyrrole electrode material, with a high energy density of 707 W h kg-1 at a power density of 32 000 W kg-1 and a current density of 8 A g-1. The 81.6% capacitance retention maintained after 1000 cycles revealed the acceptable cycling capacity of the proposed supramolecular supercapacitor system, which demonstrated good performance even at a low temperature of -20 °C.