The Making of a Flight Feather: Bio-architectural Principles and Adaptation.

The evolution of flight in feathered dinosaurs and early birds over millions of years required flight feathers whose architecture features hierarchical branches. While barb-based feather forms were investigated, feather shafts and vanes are understudied. Here, we take a multi-disciplinary approach to study their molecular control and bio-architectural organizations. In rachidial ridges, epidermal progenitors generate cortex and medullary keratinocytes, guided by Bmp and transforming growth factor ß (TGF-ß) signaling that convert rachides into adaptable bilayer composite beams. In barb ridges, epidermal progenitors generate cylindrical, plate-, or hooklet-shaped barbule cells that form fluffy branches or pennaceous vanes, mediated by asymmetric cell junction and keratin expression. Transcriptome analyses and functional studies show anterior-posterior Wnt2b signaling within the dermal papilla controls barbule cell fates with spatiotemporal collinearity. Quantitative bio-physical analyses of feathers from birds with different flight characteristics and feathers in Burmese amber reveal how multi-dimensional functionality can be achieved and may inspire future composite material designs. VIDEO ABSTRACT.

Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer.

To provide a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer, we performed a comprehensive mass-spectrometry-based proteomic characterization of 174 ovarian tumors previously analyzed by The Cancer Genome Atlas (TCGA), of which 169 were high-grade serous carcinomas (HGSCs). Integrating our proteomic measurements with the genomic data yielded a number of insights into disease, such as how different copy-number alternations influence the proteome, the proteins associated with chromosomal instability, the sets of signaling pathways that diverse genome rearrangements converge on, and the ones most associated with short overall survival. Specific protein acetylations associated with homologous recombination deficiency suggest a potential means for stratifying patients for therapy. In addition to providing a valuable resource, these findings provide a view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC. VIDEO ABSTRACT.

A pathology foundation model for cancer diagnosis and prognosis prediction.

Histopathology image evaluation is indispensable for cancer diagnoses and subtype classification. Standard artificial intelligence methods for histopathology image analyses have focused on optimizing specialized models for each diagnostic task1,2. Although such methods have achieved some success, they often have limited generalizability to images generated by different digitization protocols or samples collected from different populations3. Here, to address this challenge, we devised the Clinical Histopathology Imaging Evaluation Foundation (CHIEF) model, a general-purpose weakly supervised machine learning framework to extract pathology imaging features for systematic cancer evaluation. CHIEF leverages two complementary pretraining methods to extract diverse pathology representations: unsupervised pretraining for tile-level feature identification and weakly supervised pretraining for whole-slide pattern recognition. We developed CHIEF using 60,530 whole-slide images spanning 19 anatomical sites. Through pretraining on 44 terabytes of high-resolution pathology imaging datasets, CHIEF extracted microscopic representations useful for cancer cell detection, tumour origin identification, molecular profile characterization and prognostic prediction. We successfully validated CHIEF using 19,491 whole-slide images from 32 independent slide sets collected from 24 hospitals and cohorts internationally. Overall, CHIEF outperformed the state-of-the-art deep learning methods by up to 36.1%, showing its ability to address domain shifts observed in samples from diverse populations and processed by different slide preparation methods. CHIEF provides a generalizable foundation for efficient digital pathology evaluation for patients with cancer.

A Feshbach resonance in collisions between triplet ground-state molecules.

Collisional resonances are important tools that have been used to modify interactions in ultracold gases, for realizing previously unknown Hamiltonians in quantum simulations1, for creating molecules from atomic gases2 and for controlling chemical reactions. So far, such resonances have been observed for atom-atom collisions, atom-molecule collisions3-7 and collisions between Feshbach molecules, which are very weakly bound8-10. Whether such resonances exist for ultracold ground-state molecules has been debated owing to the possibly high density of states and/or rapid decay of the resonant complex11-15. Here we report a very pronounced and narrow (25 mG) Feshbach resonance in collisions between two triplet ground-state NaLi molecules. This molecular Feshbach resonance has two special characteristics. First, the collisional loss rate is enhanced by more than two orders of magnitude above the background loss rate, which is saturated at the p-wave universal value, owing to strong chemical reactivity. Second, the resonance is located at a magnetic field where two open channels become nearly degenerate. This implies that the intermediate complex predominantly decays to the second open channel. We describe the resonant loss feature using a model with coupled modes that is analogous to a Fabry-Pérot cavity. Our observations provide strong evidence for the existence of long-lived coherent intermediate complexes even in systems without reaction barriers and open up the possibility of coherent control of chemical reactions.

nsDCC: dual-level contrastive clustering with nonuniform sampling for scRNA-seq data analysis.

Dimensionality reduction and clustering are crucial tasks in single-cell RNA sequencing (scRNA-seq) data analysis, treated independently in the current process, hindering their mutual benefits. The latest methods jointly optimize these tasks through deep clustering. However, contrastive learning, with powerful representation capability, can bridge the gap that common deep clustering methods face, which requires pre-defined cluster centers. Therefore, a dual-level contrastive clustering method with nonuniform sampling (nsDCC) is proposed for scRNA-seq data analysis. Dual-level contrastive clustering, which combines instance-level contrast and cluster-level contrast, jointly optimizes dimensionality reduction and clustering. Multi-positive contrastive learning and unit matrix constraint are introduced in instance- and cluster-level contrast, respectively. Furthermore, the attention mechanism is introduced to capture inter-cellular information, which is beneficial for clustering. The nsDCC focuses on important samples at category boundaries and in minority categories by the proposed nearest boundary sparsest density weight assignment algorithm, making it capable of capturing comprehensive characteristics against imbalanced datasets. Experimental results show that nsDCC outperforms the six other state-of-the-art methods on both real and simulated scRNA-seq data, validating its performance on dimensionality reduction and clustering of scRNA-seq data, especially for imbalanced data. Simulation experiments demonstrate that nsDCC is insensitive to "dropout events" in scRNA-seq. Finally, cluster differential expressed gene analysis confirms the meaningfulness of results from nsDCC. In summary, nsDCC is a new way of analyzing and understanding scRNA-seq data.

SpatialCells: automated profiling of tumor microenvironments with spatially resolved multiplexed single-cell data.

Cancer is a complex cellular ecosystem where malignant cells coexist and interact with immune, stromal and other cells within the tumor microenvironment (TME). Recent technological advancements in spatially resolved multiplexed imaging at single-cell resolution have led to the generation of large-scale and high-dimensional datasets from biological specimens. This underscores the necessity for automated methodologies that can effectively characterize molecular, cellular and spatial properties of TMEs for various malignancies. This study introduces SpatialCells, an open-source software package designed for region-based exploratory analysis and comprehensive characterization of TMEs using multiplexed single-cell data. The source code and tutorials are available at https://semenovlab.github.io/SpatialCells. SpatialCells efficiently streamlines the automated extraction of features from multiplexed single-cell data and can process samples containing millions of cells. Thus, SpatialCells facilitates subsequent association analyses and machine learning predictions, making it an essential tool in advancing our understanding of tumor growth, invasion and metastasis.

Observation of the exceptional-point-enhanced Sagnac effect.

Exceptional points (EPs) are special spectral degeneracies of non-Hermitian Hamiltonians that govern the dynamics of open systems. At an EP, two or more eigenvalues, and the corresponding eigenstates, coalesce1-3. Recently, it was predicted that operation of an optical gyroscope near an EP results in improved response to rotations4,5. However, the performance of such a system has not been examined experimentally. Here we introduce a precisely controllable physical system for the study of non-Hermitian physics and nonlinear optics in high-quality-factor microresonators. Because this system dissipatively couples counter-propagating lightwaves within the resonator, it also functions as a sensitive gyroscope for the measurement of rotations. We use our system to investigate the predicted EP-enhanced Sagnac effect4,5 and observe a four-fold increase in the Sagnac scale factor by directly measuring rotations applied to the resonator. The level of enhancement can be controlled by adjusting the system bias relative to the EP, and modelling results confirm the observed enhancement. Moreover, we characterize the sensitivity of the gyroscope near the EP. Besides verifying EP physics, this work is important for the understanding of optical gyroscopes.

Multi-organ immune-related adverse events from immune checkpoint inhibitors and their downstream implications: a retrospective multicohort study.

BACKGROUND: Understanding co-occurrence patterns and prognostic implications of immune-related adverse events is crucial for immunotherapy management. However, previous studies have been limited by sample size and generalisability. In this study, we leveraged a multi-institutional cohort and a population-level database to investigate co-occurrence patterns of and survival outcomes after multi-organ immune-related adverse events among recipients of immune checkpoint inhibitors. METHODS: In this retrospective study, we identified individuals who received immune checkpoint inhibitors between May 31, 2015, and June 29, 2022, from the Massachusetts General Hospital, Brigham and Women's Hospital, and Dana-Farber Cancer Institute (Boston, MA, USA; MGBD cohort), and between April 30, 2010, and Oct 11, 2021, from the independent US population-based TriNetX network. We identified recipients from all datasets using medication codes and names of seven common immune checkpoint inhibitors, and patients were excluded from our analysis if they had incomplete information (eg, diagnosis and medication records) or if they initiated immune checkpoint inhibitor therapy after Oct 11, 2021. Eligible patients from the MGBD cohort were then propensity score matched with recipients of immune checkpoint inhibitors from the TriNetX database (1:2) based on demographic, cancer, and immune checkpoint inhibitor characteristics to facilitate cohort comparability. We applied immune-related adverse event identification rules to identify patients who did and did not have immune-related adverse events in the matched cohorts. To reduce the likelihood of false positives, patients diagnosed with suspected immune-related adverse events within 3 months after chemotherapy were excluded. We performed pairwise correlation analyses, non-negative matrix factorisation, and hierarchical clustering to identify co-occurrence patterns in the MGBD cohort. We conducted landmark overall survival analyses for patient clusters based on predominant immune-related adverse event factors and calculated accompanying hazard ratios (HRs) and 95% CIs, focusing on the 6-month landmark time for primary analyses. We validated our findings using the TriNetX cohort. FINDINGS: We identified 15 246 recipients of immune checkpoint inhibitors from MGBD and 50 503 from TriNetX, of whom 13 086 from MGBD and 26 172 from TriNetX were included in our propensity score-matched cohort. Median follow-up durations were 317 days (IQR 113-712) in patients from MGBD and 249 days (91-616) in patients from TriNetX. After applying immune-related adverse event identification rules, 8704 recipients of immune checkpoint inhibitors were retained from MGBD, of whom 3284 (37·7%) had and 5420 (62·3%) did not have immune-related adverse events, and 18 162 recipients were retained from TriNetX, of whom 5538 (30·5%) had and 12 624 (69·5%) did not have immune-related adverse events. In both cohorts, positive pairwise correlations of immune-related adverse events were commonly observed. Co-occurring immune-related adverse events were decomposed into seven factors across organs, revealing seven distinct patient clusters (endocrine, cutaneous, respiratory, gastrointestinal, hepatic, musculoskeletal, and neurological). In the MGBD cohort, the patient clusters that predominantly had endocrine (HR 0·53 [95% CI 0·40-0·70], p<0·0001) and cutaneous (0·61 [0·46-0·81], p=0·0007) immune-related adverse events had favourable overall survival outcomes at the 6-month landmark timepoint, while the other clusters either had unfavourable (respiratory: 1·60 [1·25-2·03], p=0·0001) or neutral survival outcomes (gastrointestinal: 0·86 [0·67-1·10], p=0·23; musculoskeletal: 0·97 [0·78-1·21], p=0·78; hepatic: 1·20 [0·91-1·59], p=0·19; and neurological: 1·30 [0·97-1·74], p=0·074). Similar results were found in the TriNetX cohort (endocrine: HR 0·75 [95% CI 0·60-0·93], p=0·0078; cutaneous: 0·62 [0·48-0·82], p=0·0007; respiratory: 1·21 [1·00-1·46], p=0·044), except for the neurological cluster having unfavourable (rather than neutral) survival outcomes (1·30 [1·06-1·59], p=0·013). INTERPRETATION: Reliably identifying the immune-related adverse event cluster to which a patient belongs can provide valuable clinical information for prognosticating outcomes of immunotherapy. These insights can be leveraged to counsel patients on the clinical impact of their individual constellation of immune-related adverse events and ultimately develop more personalised surveillance and mitigation strategies. FUNDING: US National Institutes of Health.

Metabolic differences in MSTN and FGF5 dual-gene edited sheep muscle cells during myogenesis.

Dynamic metabolic reprogramming occurs at different stages of myogenesis and contributes to the fate determination of skeletal muscle satellite cells (MuSCs). Accumulating evidence suggests that mutations in myostatin (MSTN) have a vital role in regulating muscle energy metabolism. Here, we explored the metabolic reprogramming in MuSCs and myotube cells in MSTN and FGF5 dual-gene edited sheep models prepared previously, and also focused on the metabolic alterations during myogenic differentiation of MuSCs. Our study revealed that the pathways of nucleotide metabolism, pantothenate and CoA biosynthesis were weakened, while the unsaturated fatty acids biosynthesis were strengthened during myogenic differentiation of sheep MuSCs. The MSTN and FGF5 dual-gene editing mainly inhibited nucleotide metabolism and biosynthesis of unsaturated fatty acids in sheep MuSCs, reduced the number of lipid droplets in per satellite cell, and promoted the pentose phosphate pathway, and the interconversion of pentose and glucuronate. The MSTN and FGF5 dual-gene editing also resulted in the inhibition of nucleotide metabolism and TCA cycle pathway in differentiated myotube cells. The differential metabolites we identified can be characterized as biomarkers of different cellular states, and providing a new reference for MSTN and FGF5 dual-gene editing in regulation of muscle development. It may also provide a reference for the development of muscle regeneration drugs targeting biomarkers.

The combination of SHP099 inhibits the malignant biological behavior of L-OHP/5-FU-resistant colorectal cancer cells by regulating energy metabolism reprogramming.

BACKGROUND AND OBJECTIVE: Colorectal cancer (CRC) is one of the most common malignancies in China. At present, there is a problem that the CRC treatment drugs SHP099, L-OHP and 5-FU are insensitive to tumor cells. Combination medication is an important means to solve the insensitivity of medication alone. The purpose of this project was to explore the effect and molecular mechanism of SHP099 combination on the malignant biological behavior of L-OHP/5-FU resistant strains of CRC. METHODS: HT29 and SW480 cells were cultured in media supplemented with L-OHP or 5-FU to establish drug-resistant strains. HT29 and SW480 drug-resistant cells were subcutaneously injected into the ventral nerves of nude mice at a dose of 5 × 106 to establish CRC drug-resistant animal models. CCK-8, Western blot, flow cytometry, Transwell and kit detection were used to detect the regulatory mechanism of energy metabolism reprogramming in drug-resistant CRC cells. RESULTS: Compared with nonresistant strains, L-OHP/5-FU-resistant strains exhibited greater metabolic reprogramming. Functionally, SHP099 can restrain the metabolic reprogramming of L-OHP/5-FU-resistant strains and subsequently restrain the proliferation, colony formation, migration and spheroid formation of L-OHP/5-FU-resistant strains. Downstream mechanistic studies have shown that SHP099 interferes with the metabolic reprogramming of L-OHP/5-FU drug-resistant strains by suppressing the PI3K/AKT pathway, thereby restraining the malignant biological behavior of L-OHP/5-FU drug-resistant strains and alleviating CRC. CONCLUSION: The combination of SHP099 can restrain the malignant biological behavior of L-OHP/5-FU-resistant CRC cells and alleviate the progression of CRC by interfering with the reprogramming of energy metabolism. This study explored the effect of SHP099 combination on dual-resistant CRC cells for the first time, and provided a new therapeutic idea for solving the problem of SHP099 insensitivity to CRC cells.

Cervical lymph node metastasis prediction from papillary thyroid carcinoma US videos: a prospective multicenter study.

BACKGROUND: Prediction of lymph node metastasis (LNM) is critical for individualized management of papillary thyroid carcinoma (PTC) patients to avoid unnecessary overtreatment as well as undesired under-treatment. Artificial intelligence (AI) trained by thyroid ultrasound (US) may improve prediction performance. METHODS: From September 2017 to December 2018, patients with suspicious PTC from the first medical center of the Chinese PLA general hospital were retrospectively enrolled to pre-train the multi-scale, multi-frame, and dual-direction deep learning (MMD-DL) model. From January 2019 to July 2021, PTC patients from four different centers were prospectively enrolled to fine-tune and independently validate MMD-DL. Its diagnostic performance and auxiliary effect on radiologists were analyzed in terms of receiver operating characteristic (ROC) curves, areas under the ROC curve (AUC), accuracy, sensitivity, and specificity. RESULTS: In total, 488 PTC patients were enrolled in the pre-training cohort, and 218 PTC patients were included for model fine-tuning (n = 109), internal test (n = 39), and external validation (n = 70). Diagnostic performances of MMD-DL achieved AUCs of 0.85 (95% CI: 0.73, 0.97) and 0.81 (95% CI: 0.73, 0.89) in the test and validation cohorts, respectively, and US radiologists significantly improved their average diagnostic accuracy (57% vs. 60%, P = 0.001) and sensitivity (62% vs. 65%, P < 0.001) by using the AI model for assistance. CONCLUSIONS: The AI model using US videos can provide accurate and reproducible prediction of cervical lymph node metastasis in papillary thyroid carcinoma patients preoperatively, and it can be used as an effective assisting tool to improve diagnostic performance of US radiologists. TRIAL REGISTRATION: We registered on the Chinese Clinical Trial Registry website with the number ChiCTR1900025592.

Operando Spectroscopy Observation of Mo Clusters-Ti3 C2 TX Catalyst/Support Interface's Dynamic Evolution in Hydrogen Evolution Reaction.

The interaction between catalyst and support plays an important role in electrocatalytic hydrogen evolution (HER), which may explain the improvement in performance by phase transition or structural remodeling. However, the intrinsic behavior of these catalysts (dynamic evolution of the interface under bias, structural/morphological transformation, stability) has not been clearly monitored, while the operando technology does well in capturing the dynamic changes in the reaction process in real time to determine the actual active site. In this paper, nitrogen-doped molybdenum atom-clusters on Ti3 C2 TX (MoACs /N-Ti3 C2 TX ) is used as a model catalyst to reveal the dynamic evolution of MoAcs on Ti3 C2 TX during the HER process. Operando X-ray absorption structure (XAS) theoretical calculation and in situ Raman spectroscopy showed that the Mo cluster structure evolves to a 6-coordinated monatomic Mo structure under working conditions, exposing more active sites and thus improving the catalytic performance. It shows excellent HER performance comparable to that of commercial Pt/C, including an overpotential of 60 mV at 10 mA cm-2 , a small Tafel slope (56 mV dec-1 ), and high activity and durability. This study provides a unique perspective for investigating the evolution of species, interfacial migration mechanisms, and sources of activity-enhancing compounds in the process of electroreduction.

ANGPTL4 accelerates ovarian serous cystadenocarcinoma carcinogenesis and angiogenesis in the tumor microenvironment by activating the JAK2/STAT3 pathway and interacting with ESM1.

BACKGROUND: Ovarian cancer (OC) is a malignant neoplasm that displays increased vascularization. Angiopoietin-like 4 (ANGPTL4) is a secreted glycoprotein that functions as a regulator of cell metabolism and angiogenesis and plays a critical role in tumorigenesis. However, the precise role of ANGPTL4 in the OC microenvironment, particularly its involvement in angiogenesis, has not been fully elucidated. METHODS: The expression of ANGPTL4 was confirmed by bioinformatics and IHC in OC. The potential molecular mechanism of ANGPTL4 was measured by RNA-sequence. We used a series of molecular biological experiments to measure the ANGPTL4-JAK2-STAT3 and ANGPTL4-ESM1 axis in OC progression, including MTT, EdU, wound healing, transwell, xenograft model, oil red O staining, chick chorioallantoic membrane assay and zebrafish model. Moreover, the molecular mechanisms were confirmed by Western blot, Co-IP and molecular docking. RESULTS: Our study demonstrates a significant upregulation of ANGPTL4 in OC specimens and its strong association with unfavorable prognosis. RNA-seq analysis affirms that ANGPTL4 facilitates OC development by driving JAK2-STAT3 signaling pathway activation. The interaction between ANGPTL4 and ESM1 promotes ANGPTL4 binding to lipoprotein lipase (LPL), thereby resulting in reprogrammed lipid metabolism and the promotion of OC cell proliferation, migration, and invasion. In the OC microenvironment, ESM1 may interfere with the binding of ANGPTL4 to integrin and vascular-endothelial cadherin (VE-Cad), which leads to stabilization of vascular integrity and ultimately promotes angiogenesis. CONCLUSION: Our findings underscore that ANGPTL4 promotes OC development via JAK signaling and induces angiogenesis in the tumor microenvironment through its interaction with ESM1.

Limited effects of xylem anatomy on embolism resistance in cycad leaves.

Drought-induced xylem embolism is a primary cause of plant mortality. Although c. 70% of cycads are threatened by extinction and extant cycads diversified during a period of increasing aridification, the vulnerability of cycads to embolism spread has been overlooked. We quantified the vulnerability to drought-induced embolism, pressure-volume curves, in situ water potentials, and a suite of xylem anatomical traits of leaf pinnae and rachises for 20 cycad species. We tested whether anatomical traits were linked to hydraulic safety in cycads. Compared with other major vascular plant clades, cycads exhibited similar embolism resistance to angiosperms and pteridophytes but were more vulnerable to embolism than noncycad gymnosperms. All 20 cycads had both tracheids and vessels, the proportions of which were unrelated to embolism resistance. Only vessel pit membrane fraction was positively correlated to embolism resistance, contrary to angiosperms. Water potential at turgor loss was significantly correlated to embolism resistance among cycads. Our results show that cycads exhibit low resistance to xylem embolism and that xylem anatomical traits - particularly vessels - may influence embolism resistance together with tracheids. This study highlights the importance of understanding the mechanisms of drought resistance in evolutionarily unique and threatened lineages like the cycads.

The Value of Primary Tumor Resection in Patients with Liver Metastases: A 10-Year Outcome.

OBJECTIVE: This study aimed to analyze the impact of primary tumor resection (PTR) on the prognosis of four common primary tumors with liver metastases, and to develop a prognostic model to visualize the PTR benefit rate of patients with liver metastases. MATERIALS AND METHODS: Patients diagnosed with colorectal cancer liver metastases (CRLM), pancreatic cancer liver metastases (PLM), gastric cancer liver metastases (GLM), and breast cancer liver metastases (BLM) between 2004 and 2015 were retrospectively reviewed from the Surveillance, Epidemiology, and End Results (SEER) database and assigned to either the surgery or non-surgery groups. A 1:1 propensity score matching (PSM) was performed. Surgical patients who survived longer than the median cancer-specific survival (CSS) time for non-surgery patients constituted the benefit group. Logistic regression was conducted to explore the independent factors affecting surgical benefit, and a nomogram was established. RESULTS: A total of 21,928 patients with liver metastases were included. After PSM for surgery and non-surgery patients, we found that PTR had a significant impact on the overall survival (OS) and CSS of CRLM, PLM, and BLM patients. In CRLM patients, age (p < 0.001), primary site (p = 0.006), grade (p = 0.009), N stage (p = 0.034), and histology (p = 0.006) affected the surgical benefit. In BLM patients, the independent factors were age (p = 0.002), race (p = 0.020), and radiotherapy (p = 0.043). And in PLM patients, chemotherapy was an independent factor associated with a survival benefit from PTR. CONCLUSION: PTR improved OS and CSS in patients with CRLM, PLM, and BLM. A predictive model was established to identify suitable candidates for PTR in CRLM patients.

Fast data processing method for multispectral radiation thermometry based on Euclidean distance optimization.

This study presents a fast and accurate data processing method for multispectral radiation thermometry that can accurately measure the true temperature of steel materials without requiring a priori emissivity model. The method generates a temperature matrix by inputting emissivity values at different wavelengths and selects a reference vector from the matrix. Then, it rearranges the temperature matrices at other wavelengths and calculates the Euclidean distance between each column element of the rearranged matrix and the reference vector. The method uses an unconstrained optimization technique to minimize the Euclidean distance and obtain the true temperature and emissivity of the object simultaneously. We evaluate the performance of the method by simulation and experiment in the response band of 1.4 ∼ 2.5 µm and temperature range of 873 ∼ 1173 K. The simulation results indicate that the relative error of the inverted temperature is within 0.229%, and the average computation time is less than 112.301 ms. The experimental results show that the maximum temperature error during the measurement process is 0.813%. Our method provides a feasible and efficient solution for real-time temperature measurement of steel materials.

Ultra-high Q resonances based on zero group-velocity modes accompanied by bound states in the continuum in 2D photonic crystal slabs.

Optical resonators made of 2D photonic crystal (PhC) slabs provide efficient ways to manipulate light at the nanoscale through small group-velocity modes with low radiation losses. The resonant modes in periodic photonic lattices are predominantly limited by nonleaky guided modes at the boundary of the Brillouin zone below the light cone. Here, we propose a mechanism for ultra-high Q resonators based on the bound states in the continuum (BICs) above the light cone that have zero-group velocity (ZGV) at an arbitrary Bloch wavevector. By means of the mode expansion method, the construction and evolution of avoided crossings and Friedrich-Wintgen BICs are theoretically investigated at the same time. By tuning geometric parameters of the PhC slab, the coalescence of eigenfrequencies for a pair of BIC and ZGV modes is achieved, indicating that the waveguide modes are confined longitudinally by small group-velocity propagation and transversely by BICs. Using this mechanism, we engineer ultra-high Q nanoscale resonators that can significantly suppress the radiative losses, despite the operating frequencies above the light cone and the momenta at the generic k point. Our work suggests that the designed devices possess potential applications in low-threshold lasers and enhanced nonlinear effects.

Multispectral radiation thermometry platform based on wireless data transmission.

In metal smelting, precise temperature control is of vital importance for reaction rates, efficiency, and product quality. Traditional methods such as thermocouples have inherent limitations, but multispectral radiation thermometry (MRT) offers high resolution and reliability. This paper proposes a multispectral radiation thermometry platform featuring wireless data transmission, which enables remote data transfer and precise temperature measurements. The platform was meticulously calibrated, and six common emissivity models were inverted with high accuracy. The results of temperature measurements conducted at a copper smelting site demonstrated an excellent degree of agreement with those obtained using disposable thermocouples. The platform has the potential to be applied in harsh environments, offering, to our knowledge, a novel approach to temperature measurement in metal smelting processes.

Integrated approach for simultaneously measuring thermophysical parameters of semi-transparent materials.

To concurrently determine the thermophysical parameters of semi-transparent materials, a novel, to the best of our knowledge, integrated approach for concurrent measurement is proposed. In the measurement setup, a high-temperature radiation source and a beam reducer are employed to minimize the influence of background radiation. In order to differentiate between the transmitted and emitted radiation in the detection signal, the radiation signals from the radiation source are measured under four different conditions, enabling the calculation of transmissivity, emissivity, and reflectivity. The reliability and accuracy of the measurement method are validated by the thermophysical parameters of sapphire, and the results demonstrate a strong agreement between the measured data and previous findings. The combined uncertainties of transmissivity and emissivity for the sapphire at 753 K are estimated, highlighting the novel contribution of this method in investigating the thermophysical parameters of semi-transparent materials.

Experimental Quantum Non-Gaussian Coincidences of Entangled Photons.

Quantum non-Gaussianity, a more potent and highly useful form of nonclassicality, excludes all convex mixtures of Gaussian states and Gaussian parametric processes generating them. Here, for the first time, we conclusively test quantum non-Gaussian coincidences of entangled photon pairs with the Clauser-Horne-Shimony-Holt-Bell factor S=2.328±0.004 from a single quantum dot with a depth up to 0.94±0.02 dB. Such deterministically generated photon pairs fundamentally overcome parametric processes by reducing crucial multiphoton errors. For the quantum non-Gaussian depth of the unheralded (heralded) single-photon state, we achieve the value of 8.08±0.05 dB (19.06±0.29 dB). Our Letter experimentally certifies the exclusive quantum non-Gaussianity properties highly relevant for optical sensing, communication, and computation.