Multi-scale window transformer for cervical cytopathology image recognition

Cervical cancer is a major global health issue, particularly in developing countries where access to healthcare is limited. Early detection of pre-cancerous lesions is crucial for successful treatment and reducing mortality rates. However, traditional screening and diagnostic processes require cytopathology doctors to manually interpret a huge number of cells, which is time-consuming, costly, and prone to human experiences. In this paper, we propose a Multi-scale Window Transformer (MWT) for cervical cytopathology image recognition. We design multi-scale window multi-head self-attention (MW-MSA) to simultaneously integrate cell features of different scales. Small window self-attention is used to extract local cell detail features, and large window self-attention aims to integrate features from smaller-scale window attention to achieve window-to-window information interaction. Our design enables long-range feature integration but avoids whole image self-attention (SA) in ViT or twice local window SA in Swin Transformer. We find convolutional feed-forward networks (CFFN) are more efficient than original MLP-based FFN for representing cytopathology images. Our overall model adopts a pyramid architecture. We establish two multi-center cervical cell classification datasets of two-category 192,123 images and four-category 174,138 images. Extensive experiments demonstrate that our MWT outperforms state-of-the-art general classification networks and specialized classifiers for cytopathology images in the internal and external test sets. The results on large-scale datasets prove the effectiveness and generalization of our proposed model. Our work provides a reliable cytopathology image recognition method and helps establish computer-aided screening for cervical cancer. Our code is available at https://github.com/nmyz669/MWT, and our web service tool can be accessed at https://huggingface.co/spaces/nmyz/MWTdemo.

Non-Gaussian anomalous diffusion of optical vortices

Anomalous diffusion of different particlelike entities, the deviation from typical Brownian motion, is ubiquitous in complex physical and biological systems. While optical vortices move randomly in evolving speckle fields, optical vortices have only been observed to exhibit pure Brownian motion in random speckle fields. Here we present direct experimental evidence of the anomalous diffusion of optical vortices in temporally varying speckle patterns from multiple-scattering viscoelastic media. Moreover, we observe two characteristic features, i.e., the self-similarity and the antipersistent correlation of the optical vortex motion, indicating that the mechanism of the observed subdiffusion of optical vortices can only be attributed to fractional Brownian motion (FBM). We further demonstrate that the vortex displacements exhibit a non-Gaussian heavy-tailed distribution. Additionally, we modulate the extent of subdiffusion, such as diffusive scaling exponents, and the non-Gaussianity of optical vortices by altering the viscoelasticity of samples. The discovery of the complex FBM but non-Gaussian subdiffusion of optical vortices may not only offer insight into certain fundamental physics, including the anomalous diffusion of vortices in fluids and the decoupling between Brownianity and Gaussianity, but also suggest a strong potential for utilizing optical vortices as tracers in microrheology instead of the introduced exogenous probe particles in particle tracking microrheology.

Visualizable intracardiac flow pattern in fetuses with congenital heart defect: pilot study of blood speckle-tracking echocardiography

OBJECTIVES

Blood-flow pattern is an essential factor in cardiovascular development. Recently, blood speckle-tracking echocardiography (BST) based on high-frame-rate ultrasound has emerged as a promising technique for the assessment of blood-flow patterns and properties. The objectives of this study were to determine the feasibility of BST in the fetus and to assess intracardiac blood-flow patterns of fetuses with a congenital heart defect (CHD) using this technique.

METHODS

This was a prospective study consisting of 35 normal fetuses, 35 fetuses with left-sided obstructive lesion (LSOL) and 35 fetuses with right-sided obstructive lesion (RSOL). BST images of fetal intracardiac regions of interest (ROIs), including the left ventricle (LV), right ventricle (RV), ascending aorta (AAo), aortic arch (AA), descending aorta (DAo) and pulmonary artery (PA), were obtained and analyzed. The feasibility of BST was assessed, and blood-flow pattern and number of vortices in the ROIs were recorded.

RESULTS

The median gestational age of the fetuses was 24.7 weeks (range, 19.6-34.3 weeks). BST was feasible in 81.6% of cases, and the cut-off value of depth for an adequate BST image was ≤ 7.9 cm. There were no differences in the presence of vortex/turbulent blood flow in the LV or RV among the three groups. Vortex/turbulent blood flow in the AAo was detected in 0% (0/35), 14.3% (5/35) and 57.1% (20/35) of cases in the control, LSOL and RSOL groups, respectively. The respective values were 5.7% (2/35), 14.3% (5/35) and 51.4% (18/35) for the AA; 0% (0/35), 48.6% (17/35) and 0% (0/35) for the DAo; and 0% (0/35), 40.0% (14/35) and 51.4% (18/35) for the PA. With the exception of the DAo in the RSOL group, vortex/turbulent flow in the great artery ROIs was significantly more common in the LSOL and RSOL groups than in controls (P < 0.01). In the LSOL group, the number of vortices in the AAo, AA, DAo and PA was significantly greater compared with that in controls (P < 0.01). In the RSOL group, the number of vortices in the LV, AAo, AA and PA was significantly greater compared with that in controls (P < 0.01).

CONCLUSIONS

Fetuses with CHD were more likely to exhibit vortex/turbulent blood flow and increased number of vortices in the great arteries compared with healthy controls. Further research is needed to determine the biomechanical effect of blood-flow patterns, especially vortex flow, on fetal cardiovascular structure and function. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Improved Measurement of the Evolution of the Reactor Antineutrino Flux and Spectrum at Daya Bay

Reactor neutrino experiments play a crucial role in advancing our knowledge of neutrinos. In this Letter, the evolution of the flux and spectrum as a function of the reactor isotopic content is reported in terms of the inverse-beta-decay yield at Daya Bay with 1958 days of data and improved systematic uncertainties. These measurements are compared with two signature model predictions: the Huber-Mueller model based on the conversion method and the SM2018 model based on the summation method. The measured average flux and spectrum, as well as the flux evolution with the ^{239}Pu isotopic fraction, are inconsistent with the predictions of the Huber-Mueller model. In contrast, the SM2018 model is shown to agree with the average flux and its evolution but fails to describe the energy spectrum. Altering the predicted inverse-beta-decay spectrum from ^{239}Pu fission does not improve the agreement with the measurement for either model. The models can be brought into better agreement with the measurements if either the predicted spectrum due to ^{235}U fission is changed or the predicted ^{235}U, ^{238}U, ^{239}Pu, and ^{241}Pu spectra are changed in equal measure.

Precision Measurement of Reactor Antineutrino Oscillation at Kilometer-Scale Baselines by Daya Bay

We present a new determination of the smallest neutrino mixing angle θ_{13} and the mass-squared difference Δm_{32}^{2} using a final sample of 5.55×10^{6} inverse beta-decay (IBD) candidates with the final-state neutron captured on gadolinium. This sample is selected from the complete dataset obtained by the Daya Bay reactor neutrino experiment in 3158 days of operation. Compared to the previous Daya Bay results, selection of IBD candidates has been optimized, energy calibration refined, and treatment of backgrounds further improved. The resulting oscillation parameters are sin^{2}2θ_{13}=0.0851±0.0024, Δm_{32}^{2}=(2.466±0.060)×10^{-3}  eV^{2} for the normal mass ordering or Δm_{32}^{2}=-(2.571±0.060)×10^{-3}  eV^{2} for the inverted mass ordering.

Ten-kilohertz two-photon microscopy imaging of single-cell dendritic activity and hemodynamics in vivo

Significance

The studying of rapid neuronal signaling across large spatial scales in intact, living brains requires both high temporal resolution and versatility of the measurement device.

Aim

We introduce a high-speed two-photon microscope based on a custom-built acousto-optic deflector (AOD). This microscope has a maximum line scan frequency of 400 kHz and a maximum frame rate of 10,000 frames per second (fps) at 250 × 40    pixels . For stepwise magnification from population view to subcellular view with high spatial and temporal resolution, we combined the AOD with resonance-galvo (RS) scanning.

Approach

With this combinatorial device that supports both large-view navigation and small-view high-speed imaging, we measured dendritic calcium propagation velocity and the velocity of single red blood cells (RBCs).

Results

We measured dendritic calcium propagation velocity ( 80 / 62.5 - 116.7    μ m / ms ) in OGB-1-labeled single cortical neurons in mice in vivo. To benchmark the spatial precision and detection sensitivity of measurement in vivo, we also visualized the trajectories of single RBCs and found that their movement speed follows Poiseuille's law of laminar flow.

Conclusions

This proof-of-concept methodological development shows that the combination of AOD and RS scanning two-photon microscopy provides both versatility and precision for quantitative analysis of single neuronal activities and hemodynamics in vivo.

Impaired ascending aortic elasticity in fetuses with tetralogy of Fallot

OBJECTIVES

Aortic wall stiffness has been reported in infants with tetralogy of Fallot (ToF) and may contribute to long-term aortic dilation even after corrective repair surgery. However, little is known about aortic elasticity in fetuses with ToF and the association with neonatal aortic dilation. The objectives of this study were to assess measures of elasticity of the ascending aorta (AAo) in fetuses with ToF and explore the association with neonatal aortic annular dilation in this population.

METHODS

Seventy-six singleton fetuses with ToF and 76 control fetuses of singleton low-risk pregnancies were enroled into this prospective study. Fetal measures of AAo elasticity, including mean longitudinal strain (MLS), global circumferential strain (GCS) and fractional area change (FAC), were assessed by velocity vector imaging. The z-score of the aortic valve (AV) diameter at the level of the annulus, as a measure of aortic annular dilation, was determined in newborns. Logistic regression analysis was used to investigate the association between fetal measures of AAo elasticity and neonatal aortic annular dilation (defined as an AV annular z-score > 2) in cases with ToF identified prenatally.

RESULTS

Median MLS, GCS and FAC in fetuses with ToF were lower than those in normal fetuses (7.52% vs 12.15% for MLS, 22.05% vs 29.73% for GCS and 34.2% vs 48.3% for FAC, all P < 0.001). Aortic annular dilation was present in 53/76 (69.7%) newborns with ToF. After adjustment for gestational age at fetal echocardiography and birth weight, fetal MLS, GCS and FAC were independently associated with aortic annular dilation neonatally, with odds ratios of 0.66, 0.78 and 0.82, respectively (P < 0.05). The best cut-off values of these prenatal measures of AAo elasticity for predicting neonatal aortic annular dilation in fetuses with ToF were 9.02% for MLS, 23.56% for GCS and 37.2% for FAC (P < 0.001), with areas under the receiver-operating-characteristics curves of 0.94, 0.91 and 0.93, respectively.

CONCLUSION

Measures of AAo elasticity are decreased in fetuses with ToF. Impaired AAo elasticity in the fetal period is associated with aortic annular dilation postnatally. Additional research is needed to evaluate the relationship between the AAo elasticity injury pattern and degeneration of AAo elasticity under stress as well as the long-term outcome in this population. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

A review of ten years of experience using dexamethasone intravitreal implants (Ozurdex) for uveitis

Uveitis is a type of ocular inflammatory disease caused by various etiologies, for which corticosteroids are the main treatment. Dexamethasone Intravitreal implant (DEX-I) has been widely used in the treatment of uveitis across the world. Then, new indications and complications appeared. This review aims to summarize the use of DEX-I in uveitis in the past 10 years. We summarized the clinical data (baseline characteristics, efficacy and safety) and discussed controversies by retrospectively analyzing the articles and cases published in PubMed and Web of Science using the terms "Ozurdex", OR "intravitreal dexamethasone implant", AND "uveitis" from 2010 to 2022. DEX-I is effective in reducing edema, improving inflammation and improving vision when treating various conditions of uveitis including infectious, no-infectious, pediatric uveitis, and surgery-related applications. The efficacy of DEX-I as a monotherapy is related to the following: etiology and course of disease, treatment of systemic diseases, patients' toleration after multiple injections, economic situation, etc. In addition, intravitreal corticosteroids implantation may replace systemic therapy in some patients. In terms of safety, the incidence of high intraocular pressure is about 20.52%, and the incidence of cataract is about 15.51%. DEX-I can effectively treat non-infectious uveitis and some infectious uveitis such as suspected tuberculosis, and its safety is controllable. Further studies are necessary to evaluate the effect of monotherapy and to expand more indications.

Multiparameter mobile blood analysis for complete blood count utilizing contrast-enhanced defocusing imaging and machine vision

Blood analysis, through the complete blood count, is the most basic medical test for disease diagnosis. Conventional blood analysis requires bulky and expensive laboratory facilities and skilled technicians, limiting the...

Anatomical Evidence for Parasympathetic Innervation of the Renal Vasculature and Pelvis

BACKGROUND

The kidneys critically contribute to body homeostasis under the control of the autonomic nerves, which enter the kidney along the renal vasculature. Although the renal sympathetic and sensory nerves have long been confirmed, no significant anatomic evidence exists for renal parasympathetic innervation.

METHODS

We identified cholinergic nerve varicosities associated with the renal vasculature and pelvis using various anatomic research methods, including a genetically modified mouse model and immunostaining. Single-cell RNA sequencing (scRNA-Seq) was used to analyze the expression of AChRs in the renal artery and its segmental branches. To assess the origins of parasympathetic projecting nerves of the kidney, we performed retrograde tracing using recombinant adeno-associated virus (AAV) and pseudorabies virus (PRV), followed by imaging of whole brains, spinal cords, and ganglia.

RESULTS

We found that cholinergic axons supply the main renal artery, segmental renal artery, and renal pelvis. On the renal artery, the newly discovered cholinergic nerve fibers are separated not only from the sympathetic nerves but also from the sensory nerves. We also found cholinergic ganglion cells within the renal nerve plexus. Moreover, the scRNA-Seq analysis suggested that acetylcholine receptors (AChRs) are expressed in the renal artery and its segmental branches. In addition, retrograde tracing suggested vagus afferents conduct the renal sensory pathway to the nucleus of the solitary tract (NTS), and vagus efferents project to the kidney.

CONCLUSIONS

Cholinergic nerves supply renal vasculature and renal pelvis, and a vagal brain-kidney axis is involved in renal innervation.

Super-resolution Segmentation Network for Reconstruction of Packed Neurites

Neuron reconstruction can provide the quantitative data required for measuring the neuronal morphology and is crucial in brain research. However, the difficulty in reconstructing dense neurites, wherein massive labor is required for accurate reconstruction in most cases, has not been well resolved. In this work, we provide a new pathway for solving this challenge by proposing the super-resolution segmentation network (SRSNet), which builds the mapping of the neurites in the original neuronal images and their segmentation in a higher-resolution (HR) space. During the segmentation process, the distances between the boundaries of the packed neurites are enlarged, and only the central parts of the neurites are segmented. Owing to this strategy, the super-resolution segmented images are produced for subsequent reconstruction. We carried out experiments on neuronal images with a voxel size of 0.2 μm × 0.2 μm × 1 μm produced by fMOST. SRSNet achieves an average F1 score of 0.88 for automatic packed neurites reconstruction, which takes both the precision and recall values into account, while the average F1 scores of other state-of-the-art automatic tracing methods are less than 0.70.

Association between maternal oxygenation and brain growth in fetuses with left-sided cardiac obstructive lesions

OBJECTIVE

Impaired brain growth has been observed in fetuses with left-sided obstructive lesions (LSOL). Maternal oxygenation (MO) can alter fetal cerebral oxygenation and vascular reactivity. Our aim was to observe whether brain growth improves during MO in fetuses with LSOL.

METHODS

Forty-six fetuses with LSOL and 23 control fetuses were enrolled in this prospective longitudinal study. Fetuses with LSOL were subgrouped into those with MO (LSOL-MO, n = 23) and those without MO (LSOL-nMO, n = 23). Fetal head circumference (HC) and total intracranial volume (TIV) were evaluated serially at 4-week intervals. Brain biometry and growth were analyzed using linear mixed models adjusted for gestational age and sex. Spearman's correlation coefficients were calculated to identify baseline characteristics predictive of brain growth in the LSOL-MO group.

RESULTS

Duration of MO therapy had significant interaction effects on cerebral biometry in fetuses with LSOL. TIV increased more rapidly after 8 weeks of oxygen exposure and HC was larger after 16 weeks of oxygen exposure in the LSOL-MO group compared with the LSOL-nMO group (P &lt; 0.001). The change in TIV at the final time- point relative to the initial timepoint in the LSOL-MO group correlated negatively with the baseline pulsatility index of the middle cerebral artery (r = -0.58, P = 0.003) and baseline myocardial performance index of the left ventricle (r = -0.68, P &lt; 0.001).

CONCLUSIONS

TIV and HC increased faster in fetuses with LSOL which had MO compared with those that did not. Lower cerebral vascular resistance and preserved left heart function at baseline may predict greater cerebral biometric growth during MO. Additional research, including larger serial studies, is needed to confirm these preliminary findings and evaluate the clinical application of MO in this population. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Deep Underground Laboratory Measurement of ^{13}C(α,n)^{16}O in the Gamow Windows of the s and i Processes

The ^{13}C(α,n)^{16}O reaction is the main neutron source for the slow-neutron-capture process in asymptotic giant branch stars and for the intermediate process. Direct measurements at astrophysical energies in above-ground laboratories are hindered by the extremely small cross sections and vast cosmic-ray-induced background. We performed the first consistent direct measurement in the range of E_{c.m.}=0.24 to 1.9 MeV using the accelerators at the China Jinping Underground Laboratory and Sichuan University. Our measurement covers almost the entire intermediate process Gamow window in which the large uncertainty of the previous experiments has been reduced from 60% down to 15%, eliminates the large systematic uncertainty in the extrapolation arising from the inconsistency of existing datasets, and provides a more reliable reaction rate for the studies of the slow-neutron-capture and intermediate processes along with the first direct determination of the alpha strength for the near-threshold state.

Label-free hematology analysis method based on defocusing phase-contrast imaging under illumination of 415 nm light

Label-free imaging technology is a trending way to simplify and improve conventional hematology analysis by bypassing lengthy and laborious staining procedures. However, the existing methods do not well balance system complexity, data acquisition efficiency, and data analysis accuracy, which severely impedes their clinical translation. Here, we propose defocusing phase-contrast imaging under the illumination of 415 nm light to realize label-free hematology analysis. We have verified that the subcellular morphology of blood components can be visualized without complex staining due to the factor that defocusing can convert the second-order derivative distribution of samples' optical phase into intensity and the illumination of 415 nm light can significantly enhance the contrast. It is demonstrated that the defocusing phase-contrast images for the five leucocyte subtypes can be automatically discriminated by a trained deep-learning program with high accuracy (the mean F1 score: 0.986 and mean average precision: 0.980). Since this technique is based on a regular microscope, it simultaneously realizes low system complexity and high data acquisition efficiency with remarkable quantitative analysis ability. It supplies a label-free, reliable, easy-to-use, fast approach to simplifying and reforming the conventional way of hematology analysis.

First Measurement of High-Energy Reactor Antineutrinos at Daya Bay

This Letter reports the first measurement of high-energy reactor antineutrinos at Daya Bay, with nearly 9000 inverse beta decay candidates in the prompt energy region of 8-12 MeV observed over 1958 days of data collection. A multivariate analysis is used to separate 2500 signal events from background statistically. The hypothesis of no reactor antineutrinos with neutrino energy above 10 MeV is rejected with a significance of 6.2 standard deviations. A 29% antineutrino flux deficit in the prompt energy region of 8-11 MeV is observed compared to a recent model prediction. We provide the unfolded antineutrino spectrum above 7 MeV as a data-based reference for other experiments. This result provides the first direct observation of the production of antineutrinos from several high-Q_{β} isotopes in commercial reactors.

Charge and Spin Order Dichotomy in NdNiO_{2} Driven by the Capping Layer

Superconductivity in infinite-layer nickelates holds exciting analogies with that of cuprates, with similar structures and 3d-electron count. Using resonant inelastic x-ray scattering, we studied electronic and magnetic excitations and charge density correlations in Nd_{1-x}Sr_{x}NiO_{2} thin films with and without an SrTiO_{3} capping layer. We observe dispersing magnons only in the capped samples, progressively dampened at higher doping. We detect an elastic resonant scattering peak in the uncapped x=0 compound at wave vector (∼⅓,0), remindful of the charge order signal in hole doped cuprates. The peak weakens at x=0.05 and disappears in the superconducting x=0.20 film. The role of the capping on the electronic reconstruction far from the interface remains to be understood.

The long-term effect of dental treatment under general anaesthesia or physical restraints on children's dental anxiety and behaviour

AIM

Dental anxiety (DA) is a common problem worldwide because it renders dental treatment in children challenging. This study aimed to evaluate the long-term effect of dental treatment under general anaesthesia (GA) or physical restraints (PR) on children's DA and behaviour.

METHODS

A total of 103 children were recruited and divided into four groups: the GA group, PR group, cooperative (CO) group, and no experience (NE) group. The face version of the Modified Child Dental Anxiety Scale and modified Venham's Clinical Anxiety and Cooperative Behaviour Rating Scale were used to evaluate the level of DA and behaviour.

CONCLUSION

Dental treatment under GA is associated with a higher risk for DA when compared with that under PR in the long term. Increased DA may lead to uncooperative dental behaviour, although the agreement is only moderate.

Joint Determination of Reactor Antineutrino Spectra from ^{235}U and ^{239}Pu Fission by Daya Bay and PROSPECT

A joint determination of the reactor antineutrino spectra resulting from the fission of ^{235}U and ^{239}Pu has been carried out by the Daya Bay and PROSPECT Collaborations. This Letter reports the level of consistency of ^{235}U spectrum measurements from the two experiments and presents new results from a joint analysis of both data sets. The measurements are found to be consistent. The combined analysis reduces the degeneracy between the dominant ^{235}U and ^{239}Pu isotopes and improves the uncertainty of the ^{235}U spectral shape to about 3%. The ^{235}U and ^{239}Pu antineutrino energy spectra are unfolded from the jointly deconvolved reactor spectra using the Wiener-SVD unfolding method, providing a data-based reference for other reactor antineutrino experiments and other applications. This is the first measurement of the ^{235}U and ^{239}Pu spectra based on the combination of experiments at low- and highly enriched uranium reactors.

Large depth-of-field fluorescence microscopy based on deep learning supported by Fresnel incoherent correlation holography

Fluorescence microscopy plays an irreplaceable role in biomedicine. However, limited depth of field (DoF) of fluorescence microscopy is always an obstacle of image quality, especially when the sample is with an uneven surface or distributed in different depths. In this manuscript, we combine deep learning with Fresnel incoherent correlation holography to describe a method to obtain significant large DoF fluorescence microscopy. Firstly, the hologram is restored by the Auto-ASP method from out-of-focus to in-focus in double-spherical wave Fresnel incoherent correlation holography. Then, we use a generative adversarial network to eliminate the artifacts introduced by Auto-ASP and output the high-quality image as a result. We use fluorescent beads, USAF target and mouse brain as samples to demonstrate the large DoF of more than 400µm, which is 13 times better than that of traditional wide-field microscopy. Moreover, our method is with a simple structure, which can be easily combined with many existing fluorescence microscopic imaging technology.

STSRNet: Self-Texture Transfer Super-Resolution and Refocusing Network

Biomedical microscopy images with high-resolution (HR) and axial information can help analysis and diagnosis. However, obtaining such images usually takes more time and economic costs, which makes it impractical in most scenarios. In this paper, we first propose a novel Self-texture Transfer Super-resolution and Refocusing Network (STSRNet) to reconstruct HR multi-focal plane (MFP) images from a single 2D low-resolution (LR) wide field image without relying on scanning or any special devices. The proposed STSRNet consists of three parts: the backbone module for extracting features, the self-texture transfer module for transferring and fusing features, and the flexible reconstruction module for SR and refocusing. Specifically, the self-texture transfer module is designed for images with self-similarity such as cytological images and it searches for similar textures within the image and transfers to help MFP reconstruction. As for reconstruction module, it is composed of multiple pluggable components, each of which is responsible for a specific focal plane, so as to performs SR and refocusing all focal planes at one time to reduce computation. We conduct extensive experiments on cytological images and the experiments show that MFP images reconstructed by STSRNet have richer details in the axial and horizontal directions than input images. At the same time, the reconstructed MFP images also perform better than single 2D wide field images on high-level tasks. The proposed method provides relatively high-quality MFP images when real MFP images cannot be obtained, which greatly expands the application potential of LR wide-field images. To further promote the development of this field, we released our cytology dataset named RSDC for more researchers to use.

Minimizing probability graph connectivity cost for discontinuous filamentary structures tracing in neuron image

Neuron tracing from optical image is critical in understanding brain function in diseases. A key problem is to trace discontinuous filamentary structures from noisy background, which is commonly encountered in neuronal and some medical images. Broken traces lead to cumulative topological errors, and current methods were hard to assemble various fragmentary traces for correct connection. In this paper, we propose a graph connectivity theoretical method for precise filamentary structure tracing in neuron image. First, we build the initial subgraphs of signals via a region-to-region based tracing method on CNN predicted probability. CNN technique removes noise interference, whereas its prediction for some elongated fragments is still incomplete. Second, we reformulate the global connection problem of individual or fragmented subgraphs under heuristic graph restrictions as a dynamic linear programming function via minimizing graph connectivity cost, where the connected cost of breakpoints are calculated using their probability strength via minimum cost path. Experimental results on challenging neuronal images proved that the proposed method outperformed existing methods and achieved similar results of manual tracing, even in some complex discontinuous issues. Performances on vessel images indicate the potential of the method for some other tubular objects tracing.

Cross-Streams Through the Ventral Posteromedial Thalamic Nucleus to Convey Vibrissal Information

Whisker detection is crucial to adapt to the environment for some animals, but how the nervous system processes and integrates whisker information is still an open question. It is well-known that two main parallel pathways through Ventral posteromedial thalamic nucleus (VPM) ascend to the barrel cortex, and classical theory suggests that the cross-talk from trigeminal nucleus interpolaris (Sp5i) to principal nucleus (Pr5) between the main parallel pathways contributes to the multi-whisker integration in barrel columns. Moreover, some studies suggest there are other cross-streams between the parallel pathways. To confirm their existence, in this study we used a dual-viral labeling strategy and high-resolution, large-volume light imaging to get the complete morphology of individual VPM neurons and trace their projections. We found some new thalamocortical projections from the ventral lateral part of VPM (VPMvl) to barrel columns. In addition, the retrograde-viral labeling and imaging results showed there were the large trigeminothalamic projections from Sp5i to the dorsomedial section of VPM (VPMdm). Our results reveal new cross-streams between the parallel pathways through VPM, which may involve the execution of multi-whisker integration in barrel columns.

Foreground Estimation in Neuronal Images With a Sparse-Smooth Model for Robust Quantification

3D volume imaging has been regarded as a basic tool to explore the organization and function of the neuronal system. Foreground estimation from neuronal image is essential in the quantification and analysis of neuronal image such as soma counting, neurite tracing and neuron reconstruction. However, the complexity of neuronal structure itself and differences in the imaging procedure, including different optical systems and biological labeling methods, result in various and complex neuronal images, which greatly challenge foreground estimation from neuronal image. In this study, we propose a robust sparse-smooth model (RSSM) to separate the foreground and the background of neuronal image. The model combines the different smoothness levels of the foreground and the background, and the sparsity of the foreground. These prior constraints together contribute to the robustness of foreground estimation from a variety of neuronal images. We demonstrate the proposed RSSM method could promote some best available tools to trace neurites or locate somas from neuronal images with their default parameters, and the quantified results are similar or superior to the results that generated from the original images. The proposed method is proved to be robust in the foreground estimation from different neuronal images, and helps to improve the usability of current quantitative tools on various neuronal images with several applications.

StainNet: A Fast and Robust Stain Normalization Network

Stain normalization often refers to transferring the color distribution to the target image and has been widely used in biomedical image analysis. The conventional stain normalization usually achieves through a pixel-by-pixel color mapping model, which depends on one reference image, and it is hard to achieve accurately the style transformation between image datasets. In principle, this difficulty can be well-solved by deep learning-based methods, whereas, its complicated structure results in low computational efficiency and artifacts in the style transformation, which has restricted the practical application. Here, we use distillation learning to reduce the complexity of deep learning methods and a fast and robust network called StainNet to learn the color mapping between the source image and the target image. StainNet can learn the color mapping relationship from a whole dataset and adjust the color value in a pixel-to-pixel manner. The pixel-to-pixel manner restricts the network size and avoids artifacts in the style transformation. The results on the cytopathology and histopathology datasets show that StainNet can achieve comparable performance to the deep learning-based methods. Computation results demonstrate StainNet is more than 40 times faster than StainGAN and can normalize a 100,000 × 100,000 whole slide image in 40 s.

Morphological diversity of single neurons in molecularly defined cell types

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits.

The Efficacy of Pyrotinib as a Third- or Higher-Line Treatment in HER2-Positive Metastatic Breast Cancer Patients Exposed to Lapatinib Compared to Lapatinib-Naive Patients: A Real-World Study

Background: Pyrotinib is a novel irreversible pan-ErbB receptor tyrosine kinase inhibitor. Evidence of the efficacy of pyrotinib-based treatments for HER2-positive metastatic breast cancer (MBC) in patients exposed to lapatinib is limited.

Methods: Ninety-four patients who received pyrotinib as a third- or higher-line treatment for HER2-positive MBC were included in this retrospective study. The primary and secondary endpoints were overall survival (OS) and progression‐free survival (PFS). Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) analysis were implemented to balance important patient characteristics between groups.

Results: Thirty (31.9%) patients were pretreated with lapatinib and subsequently received pyrotinib as an anti-HER2 treatment, and 64 (68.1%) patients did not receive this treatment. The OS and PFS indicated a beneficial trend in lapatinib-naive group compared to lapatinib-treated group in either the original cohort (PFS: 9.02 vs 6.36 months, p = 0.05; OS: 20.73 vs 14.35 months, p = 0.08) or the PSM (PFS: 9.02 vs 6.08 months, p = 0.07; OS: 19.07 vs 18.00 months, p = 0.61) or IPTW (PFS: 9.90 vs 6.17 months, p = 0.05; OS: 19.53 vs 15.10 months, p = 0.08) cohorts. Subgroup analyses demonstrated lapatinib treatment-related differences in PFS in the premenopausal subgroup and the no prior trastuzumab treatment subgroup, but no significant differences were observed in OS.

Conclusion: Pyrotinib-based therapy demonstrated promising effects in HER2-positive MBC patients in a real-world study, especially in lapatinib-naive patients, and also some activity in lapatinib-treated patients.

Automated Neuron Tracing Using Content-Aware Adaptive Voxel Scooping on CNN Predicted Probability Map

Neuron tracing, as the essential step for neural circuit building and brain information flow analyzing, plays an important role in the understanding of brain organization and function. Though lots of methods have been proposed, automatic and accurate neuron tracing from optical images remains challenging. Current methods often had trouble in tracing the complex tree-like distorted structures and broken parts of neurite from a noisy background. To address these issues, we propose a method for accurate neuron tracing using content-aware adaptive voxel scooping on a convolutional neural network (CNN) predicted probability map. First, a 3D residual CNN was applied as preprocessing to predict the object probability and suppress high noise. Then, instead of tracing on the binary image produced by maximum classification, an adaptive voxel scooping method was presented for successive neurite tracing on the probability map, based on the internal content properties (distance, connectivity, and probability continuity along direction) of the neurite. Last, the neuron tree graph was built using the length first criterion. The proposed method was evaluated on the public BigNeuron datasets and fluorescence micro-optical sectioning tomography (fMOST) datasets and outperformed current state-of-art methods on images with neurites that had broken parts and complex structures. The high accuracy tracing proved the potential of the proposed method for neuron tracing on large-scale.

Expansion tomography for large volume tissue imaging with nanoscale resolution

Expansion microscopy enables conventional diffraction limit microscopy to achieve super-resolution imaging. However, the enlarged tissue lacks an objective lens with sufficient working distance that can image tissues with whole-brain-scale coverage. Here, we present expansion tomography (ExT) to solve this problem. We have established a modified super-absorbent hydrogel (ExT gel) that possesses high mechanical strength and enables serial sectioning. ExT gel enables tissue and cell imaging and is compatible with various fluorescent labeling strategies. Combining with the high-throughput light-sheet tomography (HLTP) system, we have shown the capability of large volume imaging with nanoscale resolution of mouse brain intact neuronal circuits. The ExT method would allow image samples to support super-resolution imaging of intact tissues with virtually unlimited axial extensions.

Targeting STING attenuates ROS induced intervertebral disc degeneration

OBJECTIVE

DNA damage induced by ROS is considered one of the main causes of nucleus pulposus (NP) cells degeneration during the progression of intervertebral disc degeneration (IVDD). cGAS-STING pathway acts as DNA-sensing mechanism for monitoring DNA damage. Recent studies have proved that cGAS-STING contributes to the development of various diseases by inducing inflammation, senescence, and apoptosis. This work explored the role of STING, the main effector of cGAS-STING signaling pathway, in NP degeneration.

METHOD

Immunohistochemistry was conducted to measure STING protein levels in the nucleus pulposus tissues from human and puncture-induced IVDD rat models. TBHP induces degeneration of nucleus pulposus cells in vitro. For in vivo experiments, lv-NC or lv-STING were injected into the central intervertebral disc space. The degeneration level of IVDD was assessed by MRI, X-ray, HE, and Safranin O staining.

RESULTS

We found that the expression of STING was upregulated in human and rat degenerated NP tissue as well as in TBHP-treated NP cells. Overexpression of STING promoted the degradation of extracellular matrix; it also promoted apoptosis and senescence of TBHP-treated and untreated NP cells. Knock-down of STING significantly reversed these effects. Mechanistically, STING activated IRF3, whereas blockage of IRF3 attenuated STING-induced apoptosis, senescence and ECM degradation. In vivo experiments revealed that STING knock-down alleviated puncture-induced IVDD development.

CONCLUSION

STING promotes IVDD progress via IRF3, while suppression of STING may be a promising treatment for IVDD.

Chemical Sectioning for Immunofluorescence Imaging

Immunofluorescence (IF) is a powerful investigative tool in biological research and medical diagnosis, whereas conventional imaging methods are always conflict between speed, contrast/resolution, and specimen volume. Chemical sectioning (CS) is an effective method to overcome the conflict, which works by chemically manipulating the off/on state of fluorescent materials and turning on only the extremely superficial surface fluorescence of tissues to realize the sectioning capacity of wide-field imaging. However, the current mechanism of CS is only applicable to samples labeled with pH-sensitive fluorescent proteins and still cannot fulfill samples immunolabeled with frequently used commercial fluorescent dyes. Here, immunofluorescence chemical sectioning (IF-CS) is described to present an off/on mechanism for Alexa dyes by complexation reactions, allowing CS imaging of IF labeled tissues. IF-CS enables IF freeing from out-of-focus interference in wide-field imaging and satisfying with multicolor imaging. IF-CS demonstrates the utility of the 3D submicron-resolution imaging of large immunolabeled tissues on the wide-field block-face system. IF-CS may remarkably facilitate systematic studies of refined subcellular architectures of endogenous proteins in intact biological systems.

An unsupervised style normalization method for cytopathology images

Diverse styles of cytopathology images have a negative effect on the generalization ability of automated image analysis algorithms. This article proposes an unsupervised method to normalize cytopathology image styles. We design a two-stage style normalization framework with a style removal module to convert the colorful cytopathology image into a gray-scale image with a color-encoding mask and a domain adversarial style reconstruction module to map them back to a colorful image with user-selected style. Our method enforces both hue and structure consistency before and after normalization by using the color-encoding mask and per-pixel regression. Intra-domain and inter-domain adversarial learning are applied to ensure the style of normalized images consistent with the user-selected for input images of different domains. Our method shows superior results against current unsupervised color normalization methods on six cervical cell datasets from different hospitals and scanners. We further demonstrate that our normalization method greatly improves the recognition accuracy of lesion cells on unseen cytopathology images, which is meaningful for model generalization.

GTree: an Open-source Tool for Dense Reconstruction of Brain-wide Neuronal Population

Recent technological advancements have facilitated the imaging of specific neuronal populations at the single-axon level across the mouse brain. However, the digital reconstruction of neurons from a large dataset requires months of manual effort using the currently available software. In this study, we develop an open-source software called GTree (global tree reconstruction system) to overcome the above-mentioned problem. GTree offers an error-screening system for the fast localization of submicron errors in densely packed neurites and along with long projections across the whole brain, thus achieving reconstruction close to the ground truth. Moreover, GTree integrates a series of our previous algorithms to significantly reduce manual interference and achieve high-level automation. When applied to an entire mouse brain dataset, GTree is shown to be five times faster than widely used commercial software. Finally, using GTree, we demonstrate the reconstruction of 35 long-projection neurons around one injection site of a mouse brain. GTree is also applicable to large datasets (10 TB or higher) from various light microscopes.

High throughput slanted scanning whole slide imaging system for digital pathology

In whole slide imaging (WSI), normally only a one layer imaging of the slide is performed. Autofocus at multiple positions is usually required. But defocus blur still exists due to tissue folding or specimen thickness. Repeated Z-stack scan be applied here, which, however, is too time consuming. Here, a high throughput slanted scanning WSI system is reported. In this system, the slide surface was slanted 1° relative to the focal plane. Thus, the focal plane spanned multiple layers of the sample. By moving the slide, multi-layer image data of the sample can be acquired simultaneously at a time frame comparable to conventional 1-layer imaging. With image fusion, defocus blur can be avoided. High quality and fast imaging of both cytological and histological slide specimens was demonstrated without applying aberration correction. The system can be a highly efficient way for the application of WSI in digital pathology.

Divergent Projection Patterns Revealed by Reconstruction of Individual Neurons in Orbitofrontal Cortex

The orbitofrontal cortex (OFC) is involved in diverse brain functions via its extensive projections to multiple target regions. There is a growing understanding of the overall outputs of the OFC at the population level, but reports of the projection patterns of individual OFC neurons across different cortical layers remain rare. Here, by combining neuronal sparse and bright labeling with a whole-brain florescence imaging system (fMOST), we obtained an uninterrupted three-dimensional whole-brain dataset and achieved the full morphological reconstruction of 25 OFC pyramidal neurons. We compared the whole-brain projection targets of these individual OFC neurons in different cortical layers as well as in the same cortical layer. We found cortical layer-dependent projections characterized by divergent patterns for information delivery. Our study not only provides a structural basis for understanding the principles of laminar organizations in the OFC, but also provides clues for future functional and behavioral studies on OFC pyramidal neurons.

Chemical sectioning fluorescence tomography: high-throughput, high-contrast, multicolor, whole-brain imaging at subcellular resolution

A thorough neuroanatomical study of the brain architecture is crucial for understanding its cellular compositions, connections, and working mechanisms. However, the fine- and multiscale features of neuron structures make it challenging for microscopic imaging, as it requires high contrast and high throughput simultaneously. Here, we propose chemical sectioning fluorescence tomography (CSFT) to solve this problem. By chemically switching OFF/ON the fluorescent state of the labeled proteins (FPs), we light only the top layer as thin as submicron for imaging without background interference. Combined with the wide-field fluorescence micro-optical sectioning tomography (fMOST) system, we have shown multicolor CSFT imaging. We also demonstrate mouse whole-brain imaging at the subcellular resolution, as well as the power for quantitative acquisition of synaptic-connection-related pyramidal dendritic spines and axon boutons on the brain-wide scale at the complete single-neuron level. We believe that the CSFT method would greatly facilitate our understanding of the brain-wide neuron networks.

Bi-channel image registration and deep-learning segmentation (BIRDS) for efficient, versatile 3D mapping of mouse brain

We have developed an open-source software called bi-channel image registration and deep-learning segmentation (BIRDS) for the mapping and analysis of 3D microscopy data and applied this to the mouse brain. The BIRDS pipeline includes image preprocessing, bi-channel registration, automatic annotation, creation of a 3D digital frame, high-resolution visualization, and expandable quantitative analysis. This new bi-channel registration algorithm is adaptive to various types of whole-brain data from different microscopy platforms and shows dramatically improved registration accuracy. Additionally, as this platform combines registration with neural networks, its improved function relative to the other platforms lies in the fact that the registration procedure can readily provide training data for network construction, while the trained neural network can efficiently segment-incomplete/defective brain data that is otherwise difficult to register. Our software is thus optimized to enable either minute-timescale registration-based segmentation of cross-modality, whole-brain datasets or real-time inference-based image segmentation of various brain regions of interest. Jobs can be easily submitted and implemented via a Fiji plugin that can be adapted to most computing environments.

Extending the 3D scanning range of DMD-based scanners for femtosecond lasers

Digital micromirror devices (DMDs) have shown their potential in 2-photon imaging and microfabrication as diffractive scanners for femtosecond lasers. However, the scanning range of a DMD-based scanner is decreased by the spatial filter (SF) used to block undesired diffraction orders. Instead of an SF, we present a method of introducing and correcting aberration (ICA) to reduce the effects of these undesired diffraction orders. In ICA, aberrations are introduced by optical elements, and only the aberration of the desired diffraction order is corrected by adding a compensatory phase to the scanning phase. The scanning ranges in the y and z directions can be nearly doubled when the SF is removed. We demonstrate that ICA can be conveniently applied to a previously constructed DMD-based 2-photon microscope, and the field of view can be extended at different axial positions.

UnaG as a reporter in adeno-associated virus-mediated gene transfer for biomedical imaging

Adeno-associated virus (AAV) is one of the most common gene transfer vectors, but it has a limited capacity. A smaller fluorescent protein is urgently needed since it is more suitable to act as a reporter in AAV. In this study, a bilirubin-dependent reporter smaller than EGFP, termed UnaG, was found to have the ability to label the neurons of a mouse brain as clearly as EGFP without the addition of exogenous bilirubin. We also found that UnaG's pH tolerance is better than that of EGFP; however, its fluorescence recovery after protonated quenching is not as good as that of EGFP. In addition, UnaG preserved its fluorescence better than EGFP in SeeDB clearing. Taken together, this study demonstrates that UnaG can act as a small intrinsically fluorescent reporter in the mouse brain without an additional ligand, thus providing an alternative over EGFP for AAV-mediated neuron labeling in mammals.

Community diversity and abundance of ammonia-oxidizing archaea and bacteria in shrimp pond sediment at different culture stages

AIMS

Ammonia oxidation is a significant process of nitrogen cycles in a lot of ecosystems sediments while there are few studies in shrimp culture pond (SCP) sediments. This paper attempted to explore the community diversity and abundance of ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) in SCP sediments at different culture stages.

METHODS AND RESULTS

We collected SCP sediments and analysed the community diversity and abundance of AOA and bacteria in shrimp pond sediment at different culture stages using the ammonia monooxygenase (amoA) gene with quantitative PCR (qPCR) and 16S rRNA gene sequencing. The AOB-amoA gene abundance was showed higher than AOA-amoA gene abundance in SCP sediments on Day 50 and Day 60 after shrimp larvae introducing into the pond, and the diversity of AOA in SCP sediments was higher than that of AOB. The phylogenetic tree revealed that the most of AOA were the member of Nitrosopumilus and Nitrososphaera, and the majority of AOB sequences were clustered into Nitrosospira, Nitrosomonas clusters 6a and 7. The AOA community has close relationship with total organic carbon (TOC), pH, total phosphorus (TP), nitrate reductase, urease, acid phosphatase and β-glucosidase. The AOB community was related to TOC, C/N and nitrate reductase.

CONCLUSIONS

AOA and AOB play the different ecological roles in SCP sediments at different culture stages.

SIGNIFICANCE AND IMPACT OF THE STUDY

Our results suggested that the different community diversity and abundance of AOA and AOB in SCP sediments, which may improve our ecological cognition of shrimp culture stages in SCP ecosystems.

Cloud-cloud collision as drivers of the chemical complexity in Galactic Centre molecular clouds

G+0.693-0.03 is a quiescent molecular cloud located within the Sagittarius B2 (Sgr B2) star-forming complex. Recent spectral surveys have shown that it represents one of the most prolific repositories of complex organic species in the Galaxy. The origin of such chemical complexity, along with the small-scale physical structure and properties of G+0.693-0.03, remains a mystery. In this paper, we report the study of multiple molecules with interferometric observations in combination with single-dish data in G+0.693-0.03. Despite the lack of detection of continuum source, we find small-scale (0.2 pc) structures within this cloud. The analysis of the molecular emission of typical shock tracers such as SiO, HNCO, and CH₃OH unveiled two molecular components, peaking at velocities of 57 and 75 km s^-1. They are found to be interconnected in both space and velocity. The position-velocity diagrams show features that match with the observational signatures of a cloud-cloud collision. Additionally, we detect three series of class I methanol masers known to appear in shocked gas, supporting the cloud-cloud collision scenario. From the maser emission we provide constraints on the gas kinetic temperatures (∼30-150 K) and H₂ densities (10⁴-10⁵ cm^-2). These properties are similar to those found for the starburst galaxy NGC253 also using class I methanol masers, suggested to be associated with a cloud-cloud collision. We conclude that shocks driven by the possible cloud-cloud collision is likely the most important mechanism responsible for the high level of chemical complexity observed in G+0.693-0.03.

Aberration-corrected three-dimensional non-inertial scanning for femtosecond lasers

Large aberrations are induced by non-collimated light when the convergence or divergence of the incident beam on the back-pupil plane of the objective lens is adjusted for 3D non-inertial scanning. These aberrations significantly degrade the focus quality and decrease the peak intensity of the femtosecond laser focal spot. Here, we describe an aberration-corrected 3D non-inertial scanning method for femtosecond lasers based on a digital micromirror device (DMD) that is used for both beam scanning and aberration correction. An imaging setup is used to detect the focal spot in the 3D space, and an iterative optimization algorithm is used to optimize the focal spot. We demonstrate the application of our proposed approach in two-photon imaging. With correction for the 200-µm out-of-focal plane, the optical axial resolution improves from 7.67 to 3.25 µm, and the intensity of the fluorescence signal exhibits an almost fivefold improvement when a 40× objective lens is used. This aberration-corrected 3D non-inertial scanning method for femtosecond lasers offers a new approach for a variety of potential applications, including nonlinear optical imaging, microfabrication, and optical storage.

Quality assessment of randomized controlled trial abstracts on drug therapy of periodontal disease from the abstracts published in dental Science Citation Indexed journals in the last ten years

Background

Randomized controlled trials (RCTs) provide the highest level of evidence and are likely to influence clinical decision-making. This study evaluated the reporting quality of RCT abstracts on drug therapy of periodontal disease and assessed the associated factors.

Material and Methods

The Pubmed database was searched for periodontal RCTs published in Science Citation Indexed (SCI) dental journals from 2010/01/01 to 2019/07/17. Information was extracted from the abstracts according to a modified Consolidated Standards of Reporting Trials (CONSORT) guideline checklist. The data was analyzed using descriptive statistical analysis and the statistical associations were examined using the linear regression analysis (P <0.05).

Results

This study retrieved 1715 articles and 249 of them were finally included. The average overall CONSORT score was 15.6 ± 3.4, which represented 40.9% (±0.6) of CONSORT criteria filling. The reporting rate of some items (trial design, numbers analyzed, confidence intervals, intention-to-treat analysis or per-protocol analysis, harms, registration) was less than 30%. The adequate reporting rate of some items (participants, randomization, numbers analyzed, confidence intervals, intention-to-treat analysis or per protocol analysis) was no more than 4%. None of the abstracts reported funding. According to the multivariable linear regression results, number of authors (P=0.030), word count (P <0.001), continent (P=0.003), structured format (P <0.001), type of periodontal disease (P <0.001) and international collaboration (P=0.023) have a significant association with reporting quality.

Conclusions

The quality of RCT abstracts on drug therapy of periodontal disease in SCI dental journals remained suboptimal. More efforts should be made to improve RCT abstracts reporting quality.

Key words:Abstracts, RCT, drug therapy, periodontal disease, CONSORT, reporting quality assessment.