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Rapid 3D imaging of entire organs and organisms at cellular resolution is a recurring challenge in life science. Here we report on a computational light-sheet microscopy able to achieve minute-timescale high-resolution mapping of entire macro-scale organs. Through combining a dual-side confocally-scanned Bessel light-sheet illumination which provides thinner-and-wider optical sectioning of deep tissues, with a content-aware compressed sensing (CACS) computation pipeline which further improves the contrast and resolution based on a single acquisition, our approach yields 3D images with high, isotropic spatial resolution and rapid acquisition over two-order-of-magnitude faster than conventional 3D microscopy implementations. We demonstrate the imaging of whole brain (~400 mm 3 ), entire gastrocnemius and tibialis muscles (~200 mm 3 ) of mouse at ultra-high throughput of 5~10 min per sample and post-improved subcellular resolution of ~ 1.5 μm (0.5-μm iso-voxel size). Various system-level cellular analyses, such as mapping cell populations at different brain sub-regions, tracing long-distance projection neurons over the entire brain, and calculating neuromuscular junction occupancy across whole muscle, are also readily accomplished by our method. High resolution imaging of large biological volumes typically takes a long time from hours to days. Here the authors use a Bessel light-sheet approach combined with a content-aware compressed sensing computational pipeline to image whole mouse organs at subcellular resolution in a few minutes.

For comprehensive studies of the brain structure and function, fluorescence imaging of the whole brain is essential. It requires large-scale volumetric imaging in cellular or molecular resolution, which could be quite challenging. Recent advances in tissue clearing technology (e.g. CLARITY, PACT) provide new solutions by homogenizing the refractive index of the samples to create transparency. However, it has been difficult to acquire high quality results through immunofluorescence (IF) staining on the cleared samples. To address this issue, we developed TSA-PACT, a method combining tyramide signal amplification (TSA) and PACT, to transform samples into hydrogel polymerization frameworks with covalent fluorescent biomarkers assembled. We show that TSA-PACT is able to reduce the opacity of the zebrafish brain by more than 90% with well-preserved structure. Compared to traditional method, TSA-PACT achieves approximately tenfold signal amplification and twofold improvement in signal-to-noise ratio (SNR). Moreover, both the structure and the fluorescent signal persist for at least 16 months with excellent signal retention ratio. Overall, this method improves immunofluorescence signal sensitivity, specificity and stability in the whole brain of juvenile and adult zebrafish, which is applicable for fine structural analysis, neural circuit mapping and three-dimensional cell counting.

The composition and spatial structure of the lymphoma tumor microenvironment (TME) provide key pathological insights for tumor survival and growth, invasion and metastasis, and resistance to immunotherapy. However, the 3D lymphoma TME has not been well studied owing to the limitations of current imaging techniques. In this work, we take full advantage of a series of new techniques to enable the first 3D TME study in intact lymphoma tissue. Diverse cell subtypes in lymphoma tissues were tagged using a multiplex immunofluorescence labeling technique. To optically clarify the entire tissue, immunolabeling-enabled three-dimensional imaging of solvent-cleared organs (iDISCO+), clear, unobstructed brain imaging cocktails and computational analysis (CUBIC) and stabilization to harsh conditions via intramolecular epoxide linkages to prevent degradation (SHIELD) were comprehensively compared with the ultimate dimensional imaging of solvent-cleared organs (uDISCO) approach selected for clearing lymphoma tissues. A Bessel-beam light-sheet fluorescence microscope (B-LSFM) was developed to three-dimensionally image the clarified tissues at high speed and high resolution. A customized MATLAB program was used to quantify the number and colocalization of the cell subtypes based on the acquired multichannel 3D images. By combining these cutting-edge methods, we successfully carried out high-efficiency 3D visualization and high-content cellular analyses of the lymphoma TME. Several antibodies, including CD3, CD8, CD20, CD68, CD163, CD14, CD15, FOXP3 and Ki67, were screened for labeling the TME in lymphoma tumors. The 3D imaging results of the TME from three types of lymphoma, reactive lymphocytic hyperplasia (RLN), diffuse large B-cell lymphoma (DLBCL), and angioimmunoblastic T-cell lymphoma (AITL), were quantitatively analyzed, and their cell number, localization, and spatial correlation were comprehensively revealed. We present an advanced imaging-based method for efficient 3D visualization and high-content cellular analysis of the lymphoma TME, rendering it a valuable tool for tumor pathological diagnosis and other clinical research.

Instant 3D imaging of entire organs and organisms at cellular resolution is a recurring challenge in life science. Here we report on a computational light-sheet microscopy able to achieve minute-timescale mapping of entire macro-scale organs at high spatial resolution, thereby overcoming the throughput limit of current 3D microscopy implementations. Through combining a dual-side confocally-scanned Bessel light-sheet illumination which provides thinner-and-wider optical sectioning of deep tissues, with a content-aware compressed sensing (CACS) computation pipeline which further improves the contrast and resolution based on a single acquisition, our method yields 3D images with high, isotropic spatial resolution and rapid acquisition improved by two-orders of magnitude. We demonstrate the imaging of whole brain (~400 mm3), entire gastrocnemius and tibialis muscles (~200 mm3) of mouse at subcellular resolution (0.5-μm isovoxel) and ultra-high throughput of 5~10 minutes per sample. Various system-level cellular analyses, such as mapping cell populations at different brain sub-regions, tracing long-distance projection neurons over the entire brain, and calculating neuromuscular junction occupancy across whole muscle, were also readily enabled by our method. Competing Interest Statement The authors have declared no competing interest.

Therapeutic blockade of the immune checkpoint proteins programmed cell death protein 1 (PD-1) and cytotoxic T lymphocyte antigen 4 (CTLA4) has transformed cancer treatment. However, the overall response rate to these treatments is low, suggesting that immune checkpoint activation is not the only mechanism leading to dysfunctional anti-tumour immunity. Here we show that butyrophilin-like protein 2 (BTNL2) is a potent suppressor of the anti-tumour immune response. Antibody-mediated blockade of BTNL2 attenuates tumour progression in multiple in vivo murine tumour models, resulting in prolonged survival of tumour-bearing mice. Mechanistically, BTNL2 interacts with local γδ T cell populations to promote IL-17A production in the tumour microenvironment. Inhibition of BTNL2 reduces the number of tumour-infiltrating IL-17A-producing γδ T cells and myeloid-derived suppressor cells, while facilitating cytotoxic CD8 + T cell accumulation. Furthermore, we find high BTNL2 expression in several human tumour samples from highly prevalent cancer types, which negatively correlates with overall patient survival. Thus, our results suggest that BTNL2 is a negative regulator of anti-tumour immunity and a potential target for cancer immunotherapy. Cancer cells producing ligands for the immune checkpoint molecules PD-1 and CTLA-4 is an important mechanism of tumour immune resistance. Here authors show that BTNL2 expression on cancer cells generates a dysfunctional tumour immune microenvironment via promoting IL-17A-producing γδ T cells.

Abstract Novel technologies for recovering DNA information from archaeological and historical specimens have made available an ever-increasing amount of temporally spaced genetic samples from natural populations. These genetic time series permit the direct assessment of patterns of temporal changes in allele frequencies and hold the promise of improving power for the inference of selection. Increased time resolution can further facilitate testing hypotheses regarding the drivers of past selection events such as the incidence of plant and animal domestication. However, studying past selection processes through ancient DNA (aDNA) still involves considerable obstacles such as postmortem damage, high fragmentation, low coverage, and small samples. To circumvent these challenges, we introduce a novel Bayesian framework for the inference of temporally variable selection based on genotype likelihoods instead of allele frequencies, thereby enabling us to model sample uncertainties resulting from the damage and fragmentation of aDNA molecules. Also, our approach permits the reconstruction of the underlying allele frequency trajectories of the population through time, which allows for a better understanding of the drivers of selection. We evaluate its performance through extensive simulations and demonstrate its utility with an application to the ancient horse samples genotyped at the loci for coat coloration. Our results reveal that incorporating sample uncertainties can further improve the inference of selection.

The standard approach to diagnosing idiopathic pulmonary fibrosis (IPF) includes identifying the usual interstitial pneumonia (UIP) pattern via high resolution computed tomography (HRCT) or lung biopsy and excluding known causes of interstitial lung disease (ILD). However, limitations of manual interpretation of lung imaging, along with other reasons such as lack of relevant knowledge and non-specific symptoms have hindered the timely diagnosis of IPF. This review proposes the definition of early IPF, emphasizes the diagnostic urgency of early IPF, and highlights current diagnostic strategies and future prospects for early IPF. The integration of artificial intelligence (AI), specifically machine learning (ML) and deep learning (DL), is revolutionizing the diagnostic procedure of early IPF by standardizing and accelerating the interpretation of thoracic images. Innovative bronchoscopic techniques such as transbronchial lung cryobiopsy (TBLC), genomic classifier, and endobronchial optical coherence tomography (EB-OCT) provide less invasive diagnostic alternatives. In addition, chest auscultation, serum biomarkers, and susceptibility genes are pivotal for the indication of early diagnosis. Ongoing research is essential for refining diagnostic methods and treatment strategies for early IPF.

In this paper, the accelerated Chambolle projection algorithms based on Frank–Wolfe have been proposed. For solving the image restoration under the additive Gaussian noise, the Chambolle projection method (CP) is widely used. However, the projection operator has a large computational cost and complex form. By means of the Frank–Wolfe method, this projection operation can be greatly simplified. We propose two new algorithms, called Chambolle projection based on Frank–Wolfe (CP–FW) and Chambolle projection based on accelerated Frank–Wolfe (CP–AFW). They have a fast convergence rate and low computation cost. Furthermore, we extend the new algorithms to deal with the Poisson noise. The convergence of the new algorithms is discussed, and results of the experiment show their effectiveness and efficiency.

Promising thermoelectric materials are usually those of “phonon‐glass electron‐crystal” (PGEC) compounds, with low thermal conductivity and high carrier mobility. In metallic materials, strong electron‐phonon interaction usually causes an increase of Seebeck coefficient (S) at low temperature, due to an extra electrical current driven by heat‐carrying phonons, named phonon drag effect. Here, this study reports that single crystalline metallic Mg3Bi2 has low lattice thermal conductivity of ≈0.49 W m−1 K−1 at 285 K, and corresponding mean free path of phonons (Lph) is ≈0.48 nm, with carrier mobility of ≈54.2 cm2 V−1 s−1 around room temperature. It is found that S exhibits an increase as a “hump” ≈20 K, and phonon drag effect (Sph) contributes to ≈80%, significantly higher than diffusive electrons. Meanwhile, Sph is positively proportional to Lph, where coefficient of Sph/Lph is ≈4.6 × 102 µV K−1 µm−1, twice that of CrSb2 and FeSb2, and relative strength of electron‐phonon interaction is ≈0.12. The Lph‐intercept of Sph/Lph approaches to ≈4.68 nm, where phonons can be strongly scattered before interacting with electrons, leading to a negligible phonon drag effect. The findings shed light on fundamental understanding of thermoelectric transport and exploring novel thermoelectric materials. In this work, low lattice thermal conductivity and high carrier mobility are revealed in single crystalline Mg3Bi2, a promising thermoelectric material. An increase of thermopower as a “hump” ≈20 K is found, where phonon drag effect contributes large portion by replacing diffusive electrons. A high coefficient of phonons driving thermopower is discovered due to its strong electron‐phonon interaction.

To date, several molecules have been found to facilitate iron influx, while the types of iron influx channels remain to be elucidated. Here, Piezo1 channel was identified as a key iron transporter in response to mechanical stress. Piezo1-mediated iron overload disturbed iron metabolism and exaggerated ferroptosis in nucleus pulposus cells (NPCs). Importantly, Piezo1-induced iron influx was independent of the transferrin receptor (TFRC), a well-recognized iron gatekeeper. Furthermore, pharmacological inactivation of Piezo1 profoundly reduced iron accumulation, alleviated mitochondrial ROS, and suppressed ferroptotic alterations in stimulation of mechanical stress. Moreover, conditional knockout of Piezo1 (Col2a1-CreERT Piezo1flox/flox) attenuated the mechanical injury-induced intervertebral disc degeneration (IVDD). Notably, the protective effect of Piezo1 deficiency in IVDD was dampened in Piezo1/Gpx4 conditional double knockout (cDKO) mice (Col2a1-CreERT Piezo1flox/flox/Gpx4flox/flox). These findings suggest that Piezo1 is a potential determinant of iron influx, indicating that the Piezo1-iron-ferroptosis axis might shed light on the treatment of mechanical stress-induced diseases.