m6A Reader YTHDC1 Inhibits Ferroptosis and Radiosensitivity by Promoting SREBF1 mRNA Nuclear Export in Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

Radioresistance is the main reason for nasopharyngeal carcinoma (NPC) recurrence leading to treatment failure, and inducing ferroptosis has gradually been a new way to enhance radiosensitivity. N6-methyladenosine (m6A) is involved in regulation of numerous biological processes. However, whether m6A affects ferroptosis in NPC is still unclear. In this study, we conducted a siRNA library screening to identify m6A reader YTHDC1 as an essential oncogene that suppressed ferroptosis and radiosensitivity by promoting SREBF1 mRNA nuclear export in nasopharyngeal carcinoma.

MATERIALS/METHODS

The expression and function of YTHDC1 were assessed via CCK8 cell viability assay, immunostaining, real-time PCR, western blot, radiation clonogenic assay and fluorescence in situ hybridization assay. Ferroptosis was determined by detecting cell viability, lipid peroxidation, abnormal mitochondrial and cell death rate. The in vivo effects of YTHDC1 were examined with RSL3 treatment or lentivirus modification of YTHDC1 expression in radiated mouse models.

RESULTS

Based on RSL3-induced ferroptotic cell death model and a siRNA library about m6A modification associated gene screening, we identified m6A reader YTHDC1 could inhibit ferroptosis as well as radiosensitivity of NPC, both in vivo and in vitro. Mechanistically, YTHDC1 protein could recognize m6A sites in the CDS region and 3' untranslated region (3'UTR) of SREBF1 mRNA and promote SREBF1 mRNA nuclear export, which finally resulted in transcriptional upregulation of genes key to ferroptosis such as SCD and FASN. Furthermore, the high expression of YTHDC1 was negatively regulated by ZNF598 via ubiquitination and associated with unfavorable survival in NPC patients due to radioresistance.

CONCLUSION

Our findings reveal the critical role of YTHDC1 specifically in inhibiting ferroptosis and radiosensitivity via m6A-dependent mechanism and provide an exploitable target and therapeutic strategy for overcoming radioresistance in NPC.

RibSeg v2: A Large-scale Benchmark for Rib Labeling and Anatomical Centerline Extraction

Automatic rib labeling and anatomical centerline extraction are common prerequisites for various clinical applications. Prior studies either use in-house datasets that are inaccessible to communities, or focus on rib segmentation that neglects the clinical significance of rib labeling. To address these issues, we extend our prior dataset (RibSeg) on the binary rib segmentation task to a comprehensive benchmark, named RibSeg v2, with 660 CT scans (15,466 individual ribs in total) and annotations manually inspected by experts for rib labeling and anatomical centerline extraction. Based on the RibSeg v2, we develop a pipeline including deep learning-based methods for rib labeling, and a skeletonization-based method for centerline extraction. To improve computational efficiency, we propose a sparse point cloud representation of CT scans and compare it with standard dense voxel grids. Moreover, we design and analyze evaluation metrics to address the key challenges of each task. Our dataset, code, and model are available online to facilitate open research at https://github.com/M3DV/RibSeg.

Immersion Fixation and Staining of Multicubic Millimeter Volumes for Electron Microscopy-Based Connectomics of Human Brain Biopsies

Connectomics allows mapping of cells and their circuits at the nanometer scale in volumes of approximately 1 mm3. Given that the human cerebral cortex can be 3 mm in thickness, larger volumes are required. Larger-volume circuit reconstructions of human brain are limited by 1) the availability of fresh biopsies; 2) the need for excellent preservation of ultrastructure, including extracellular space; and 3) the requirement of uniform staining throughout the sample, among other technical challenges. Cerebral cortical samples from neurosurgical patients are available owing to lead placement for deep brain stimulation. Described here is an immersion fixation, heavy metal staining, and tissue processing method that consistently provides excellent ultrastructure throughout human and rodent surgical brain samples of volumes 2 × 2 × 2 mm3 and up to 37 mm3 with one dimension ≤2 mm. This method should allow synapse-level circuit analysis in samples from patients with psychiatric and neurologic disorders.

3D Domain Adaptive Instance Segmentation via Cyclic Segmentation GANs

3D instance segmentation for unlabeled imaging modalities is a challenging but essential task as collecting expert annotation can be expensive and time-consuming. Existing works segment a new modality by either deploying pre-trained models optimized on diverse training data or sequentially conducting image translation and segmentation with two relatively independent networks. In this work, we propose a novel Cyclic Segmentation Generative Adversarial Network (CySGAN) that conducts image translation and instance segmentation simultaneously using a unified network with weight sharing. Since the image translation layer can be removed at inference time, our proposed model does not introduce additional computational cost upon a standard segmentation model. For optimizing CySGAN, besides the CycleGAN losses for image translation and supervised losses for the annotated source domain, we also utilize self-supervised and segmentation-based adversarial objectives to enhance the model performance by leveraging unlabeled target domain images. We benchmark our approach on the task of 3D neuronal nuclei segmentation with annotated electron microscopy (EM) images and unlabeled expansion microscopy (ExM) data. The proposed CySGAN outperforms pre-trained generalist models, feature-level domain adaptation models, and the baselines that conduct image translation and segmentation sequentially. Our implementation and the newly collected, densely annotated ExM zebrafish brain nuclei dataset, named NucExM, are publicly available at https://connectomics-bazaar.github.io/proj/CySGAN/index.html.

Dense 4D nanoscale reconstruction of living brain tissue

Three-dimensional (3D) reconstruction of living brain tissue down to an individual synapse level would create opportunities for decoding the dynamics and structure-function relationships of the brain's complex and dense information processing network; however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise ratio and prohibitive light burden in optical imaging, whereas electron microscopy is inherently static. Here we solved these challenges by developing an integrated optical/machine-learning technology, LIONESS (live information-optimized nanoscopy enabling saturated segmentation). This leverages optical modifications to stimulated emission depletion microscopy in comprehensively, extracellularly labeled tissue and previous information on sample structure via machine learning to simultaneously achieve isotropic super-resolution, high signal-to-noise ratio and compatibility with living tissue. This allows dense deep-learning-based instance segmentation and 3D reconstruction at a synapse level, incorporating molecular, activity and morphodynamic information. LIONESS opens up avenues for studying the dynamic functional (nano-)architecture of living brain tissue.

[Expression and protective effect of chemerin in idiopathic pulmonary fibrosis]

Objective: To explore the expression and the role of chemerin in idiopathic pulmonary fibrosis (IPF). Methods: Quantitative PCR and Western blotting were used to determine the mRNA and protein levels of chemerin in lung tissues from IPF patients and the controls. Clinical serum level of chemerin was analyzed by enzyme-linked immunosorbent assay. The mouse lung fibroblasts isolated and cultured in vitro were divided into the control, TGF-β, TGF-β+chemerin and chemerin groups. Immunofluorescence staining was used to observe the expression of α-smooth muscle actin (α-SMA). C57BL/6 mice were randomly divided into the control, bleomycin, bleomycin+chemerin, and chemerin groups. Masson and immunohistochemical staining were performed to evaluate the severity of pulmonary fibrosis. Expression of epithelial to mesenchymal transition (EMT) markers was detected by quantitative PCR and immunohistochemical staining in the in vitro and in vivo models of pulmonary fibrosis, respectively. Results: Compared with the control group, the expression of chemerin was downregulated in both the lung tissue and the serum of IPF patients. Immunofluorescence showed that treatment of fibroblasts with TGF-β alone resulted in a robust expression of α-SMA, whereas treatment with TGF-β and chemerin together exhibited the similar expression levels of α-SMA as the control group. Masson staining indicated that the bleomycin-induced pulmonary fibrosis model was constructed successfully, while treatment of chemerin partially alleviated the damage of lung tissue. Immunohistochemical staining showed that the expression of chemerin in the lung tissue was significantly decreased in the bleomycin group. Quantitative PCR and immunohistochemistry showed that chemerin attenuated EMT induced by TGF-β and bleomycin both in vitro and in vivo. Conclusions: The expression of chemerin was reduced in patients with IPF. Chemerin may play a protective role in the development of IPF by regulating EMT, providing a new idea for the clinical treatment of IPF.

Multiplexed volumetric CLEM enabled by antibody derivatives provides new insights into the cytology of the mouse cerebellar cortex

Mapping neuronal networks that underlie behavior has become a central focus in neuroscience. While serial section electron microscopy (ssEM) can reveal the fine structure of neuronal networks (connectomics), it does not provide the molecular information that helps identify cell types or their functional properties. Volumetric correlated light and electron microscopy (vCLEM) combines ssEM and volumetric fluorescence microscopy to incorporate molecular labeling into ssEM datasets. We developed an approach that uses small fluorescent single-chain variable fragment (scFv) immuno-probes to perform multiplexed detergent-free immuno-labeling and ssEM on the same samples. We generated eight such fluorescent scFvs that targeted useful markers for brain studies (green fluorescent protein, glial fibrillary acidic protein, calbindin, parvalbumin, voltage-gated potassium channel subfamily A member 2, vesicular glutamate transporter 1, postsynaptic density protein 95, and neuropeptide Y). To test the vCLEM approach, six different fluorescent probes were imaged in a sample of the cortex of a cerebellar lobule (Crus 1), using confocal microscopy with spectral unmixing, followed by ssEM imaging of the same sample. The results show excellent ultrastructure with superimposition of the multiple fluorescence channels. Using this approach we could document a poorly described cell type in the cerebellum, two types of mossy fiber terminals, and the subcellular localization of one type of ion channel. Because scFvs can be derived from existing monoclonal antibodies, hundreds of such probes can be generated to enable molecular overlays for connectomic studies.

First Study of Reaction Ξ^{0}n→Ξ^{-}p Using Ξ^{0}-Nucleus Scattering at an Electron-Positron Collider

Using (1.0087±0.0044)×10^{10}  J/ψ events collected with the BESIII detector at the BEPCII storage ring, the process Ξ^{0}n→Ξ^{-}p is studied, where the Ξ^{0} baryon is produced in the process J/ψ→Ξ^{0}Ξ[over ¯]^{0} and the neutron is a component of the ^{9}Be, ^{12}C, and ^{197}Au nuclei in the beam pipe. A clear signal is observed with a statistical significance of 7.1σ. The cross section of the reaction Ξ^{0}+^{9}Be→Ξ^{-}+p+^{8}Be is determined to be σ(Ξ^{0}+^{9}Be→Ξ^{-}+p+^{8}Be)=(22.1±5.3_{stat}±4.5_{sys})  mb at the Ξ^{0} momentum of 0.818  GeV/c, where the first uncertainty is statistical and the second is systematic. No significant H-dibaryon signal is observed in the Ξ^{-}p final state. This is the first study of hyperon-nucleon interactions in electron-positron collisions and opens up a new direction for such research.

Precision Measurement of the Decay Σ^{+}→pγ in the Process J/ψ→Σ^{+}Σ[over ¯]^{-}

Using (10 087±44)×10^{6} J/ψ events collected with the BESIII detector, the radiative hyperon decay Σ^{+}→pγ is studied at an electron-positron collider experiment for the first time. The absolute branching fraction is measured to be (0.996±0.021_{stat}±0.018_{syst})×10^{-3}, which is lower than its world average value by 4.2 standard deviations. Its decay asymmetry parameter is determined to be -0.652±0.056_{stat}±0.020_{syst}. The branching fraction and decay asymmetry parameter are the most precise to date, and the accuracies are improved by 78% and 34%, respectively.

Multiplexed Volumetric CLEM enabled by antibody derivatives provides new insights into the cytology of the mouse cerebellar cortex

Mapping neuronal networks that underlie behavior has become a central focus in neuroscience. While serial section electron microscopy (ssEM) can reveal the fine structure of neuronal networks (connectomics), it does not provide the molecular information that helps identify cell types or their functional properties. Volumetric correlated light and electron microscopy (vCLEM) combines ssEM and volumetric fluorescence microscopy to incorporate molecular labeling into ssEM datasets. We developed an approach that uses small fluorescent single-chain variable fragment (scFv) immuno-probes to perform multiplexed detergent-free immuno-labeling and serial electron microscopy on the same samples. We generated eight such fluorescent scFvs that targeted useful markers for brain studies (GFP, GFAP, calbindin, parvalbumin, Kv1.2, VGluT1, PSD-95, and neuropeptide Y). To test the vCLEM approach, six different fluorescent probes were imaged in a sample of the cortex of a cerebellar lobule (Crus 1), using confocal microscopy with linear unmixing, followed by ssEM imaging of the same sample. The results show excellent ultrastructure and superimposition of the different fluorescence channels. We document a poorly described cell type in the cerebellum, two types of mossy fiber terminals, and the subcellular localization of ion channels. Because scFvs can be derived from existing monoclonal antibodies, hundreds of such probes can be generated to enable a wide range of connectomic studies.

Decoding of the neural representation of the visual RGB color model

RGB color is a basic visual feature. Here we use machine learning and visual evoked potential (VEP) of electroencephalogram (EEG) data to investigate the decoding features of the time courses and space location that extract it, and whether they depend on a common brain cortex channel. We show that RGB color information can be decoded from EEG data and, with the task-irrelevant paradigm, features can be decoded across fast changes in VEP stimuli. These results are consistent with the theory of both event-related potential (ERP) and P300 mechanisms. The latency on time course is shorter and more temporally precise for RGB color stimuli than P300, a result that does not depend on a task-relevant paradigm, suggesting that RGB color is an updating signal that separates visual events. Meanwhile, distribution features are evident for the brain cortex of EEG signal, providing a space correlate of RGB color in classification accuracy and channel location. Finally, space decoding of RGB color depends on the channel classification accuracy and location obtained through training and testing EEG data. The result is consistent with channel power value distribution discharged by both VEP and electrophysiological stimuli mechanisms.

Measurements of the Electric and Magnetic Form Factors of the Neutron for Timelike Momentum Transfer

We present the first measurements of the electric and magnetic form factors of the neutron in the timelike (positive q^{2}) region as function of four-momentum transfer. We explored the differential cross sections of the reaction e^{+}e^{-}→n[over ¯]n with data collected with the BESIII detector at the BEPCII accelerator, corresponding to an integrated luminosity of 354.6  pb^{-1} in total at twelve center-of-mass energies between sqrt[s]=2.0-2.95  GeV. A relative uncertainty of 18% and 12% for the electric and magnetic form factors, respectively, is achieved at sqrt[s]=2.3935  GeV. Our results are comparable in accuracy to those from electron scattering in the comparable spacelike region of four-momentum transfer. The electromagnetic form factor ratio R_{em}≡|G_{E}|/|G_{M}| is within the uncertainties close to unity. We compare our result on |G_{E}| and |G_{M}| to recent model predictions, and the measurements in the spacelike region to test the analyticity of electromagnetic form factors.

The association of serum testosterone with dyslipidemia is mediated by obesity: the Henan Rural Cohort Study

BACKGROUND AND AIMS

This study aimed to evaluate the relationships of serum testosterone with dyslipidemia and blood lipid levels and test whether obesity mediated these associations by gender in Chinese rural population.

METHODS AND RESULTS

A total of 6150 subjects were finally analyzed in this study. Serum testosterone for each subject was detected by liquid chromatography equipped with tandem mass spectrometry. Logistic regression and linear regression were employed to evaluate the associations of serum testosterone with the prevalence of dyslipidemia and blood lipid levels. Mediation analysis was conducted to identify the mediation effects of obesity on the relationship between serum testosterone and dyslipidemia. After adjusting for multiple confounders, per unit change in serum ln-testosterone levels was associated with a decreased prevalent dyslipidemia in men (odds ratio (OR): 0.785, 95% confidence interval (CI) (0.708, 0.871)). Males with the levels of serum testosterone in the third or fourth quartiles had a 49.4% (OR: 0.506, 95% CI 0.398, 0.644) or 67.1% (OR: 0.329, 95% CI 0.253, 0.428) significantly lower odds of prevalence of dyslipidemia. In addition, a onefold increase in ln-testosterone was related to a 0.043 mmol/L (95% CI 0.028, 0.059) increase in high-density lipoprotein cholesterol (HDL-C) in men. Results of the mediation analysis suggested that obesity played a partial role in the association of testosterone with dyslipidemia in men.

CONCLUSIONS

These findings suggested that serum testosterone levels were negatively associated with lipid levels and prevalent dyslipidemia, and obesity mediated the effects of serum testosterone on dyslipidemia in men, implying that obesity prevention should be highlighted to decrease the prevalence of dyslipidemia related to changes in testosterone levels.

Observation of Three Charmoniumlike States with J^{PC}=1^{--} in e^{+}e^{-}→D^{*0}D^{*-}π^{+}

The Born cross sections of the process e^{+}e^{-}→D^{*0}D^{*-}π^{+} at center-of-mass energies from 4.189 to 4.951 GeV are measured for the first time. The data samples used correspond to an integrated luminosity of 17.9  fb^{-1} and were collected by the BESIII detector operating at the BEPCII storage ring. Three enhancements around 4.20, 4.47, and 4.67 GeV are visible. The resonances have masses of 4209.6±4.7±5.9  MeV/c^{2}, 4469.1±26.2±3.6  MeV/c^{2}, and 4675.3±29.5±3.5  MeV/c^{2} and widths of 81.6±17.8±9.0  MeV, 246.3±36.7±9.4  MeV, and 218.3±72.9±9.3  MeV, respectively, where the first uncertainties are statistical and the second systematic. The first and third resonances are consistent with the ψ(4230) and ψ(4660) states, respectively, while the second one is compatible with the ψ(4500) observed in the e^{+}e^{-}→K^{+}K^{-}J/ψ process. These three charmoniumlike ψ states are observed in the e^{+}e^{-}→D^{*0}D^{*-}π^{+} process for the first time.

Synthesis, characterization, DFT studies, and adsorption properties of sulfonated starch synthesized in deep eutectic solvent

In this study, sulfonated starch (SS) was successfully synthesized using sulfamic acid as a sulfonating agent in a deep eutectic solvent (DES). Four-factor and three-level orthogonal experiments were conducted to determine the optimal preparation conditions, which were found to be a molar ratio of starch to urea of 1:20, a reaction temperature of 90 °C, a reaction time of 5 h, and a stirring speed of 200 rpm. The sulfonation reaction mechanism was extensively studied using various techniques, including Fourier transform infrared spectroscopy, elemental analysis, X-ray diffraction, molecular weight, particle distribution, X-ray photoelectron spectroscopy, scanning electron microscopy, and DFT calculations. The results showed that the sulfonation reaction slightly damaged starch granules, occurred on the surface of starch granules, and on the O6 atoms of the glucose unit. SS exhibited a wide pH range of application (5-10), a fast adsorption rate (400 s to reach adsorption equilibrium), and a high adsorption capacity (118.3 mg/g) under optimal conditions. The adsorption process of SS for methylene blue followed the pseudo-first-order kinetic model and was consistent with the Langmuir model, which was endothermic and spontaneous. The adsorption process was attributed to hydrogen bonding and electrostatic interactions.

MedMNIST v2 - A large-scale lightweight benchmark for 2D and 3D biomedical image classification

We introduce MedMNIST v2, a large-scale MNIST-like dataset collection of standardized biomedical images, including 12 datasets for 2D and 6 datasets for 3D. All images are pre-processed into a small size of 28 × 28 (2D) or 28 × 28 × 28 (3D) with the corresponding classification labels so that no background knowledge is required for users. Covering primary data modalities in biomedical images, MedMNIST v2 is designed to perform classification on lightweight 2D and 3D images with various dataset scales (from 100 to 100,000) and diverse tasks (binary/multi-class, ordinal regression, and multi-label). The resulting dataset, consisting of 708,069 2D images and 9,998 3D images in total, could support numerous research/educational purposes in biomedical image analysis, computer vision, and machine learning. We benchmark several baseline methods on MedMNIST v2, including 2D/3D neural networks and open-source/commercial AutoML tools. The data and code are publicly available at https://medmnist.com/ .

Reconstructing sources location of visual color cortex by the task-irrelevant visual stimuli through machine learning decoding

Visual color sensing is generated by electrical discharges from endocranial neuronal sources that penetrate the skull and reach to the cerebral cortex. However, the space location of the source generated by this neural mechanism remains elusive. In this paper, we emulate the generation of visual color signal by task-irrelevant stimuli to activate brain neurons, where its consequences over the cerebral cortex is experimentally tracked. We first document the changes to brain color sensing using electroencephalography (EEG), and find that the sensing classification accuracy of primary visual cortex (V1) regions was positively correlated with the space correlation of visual evoked potential (VEP) power distribution under machine learning decoding. We then explore the decoded results to trace the brain activity neural source location of EEG inversion problem and assess its reconstructive possibility. We show that visual color EEG in V1 can reconstruct endocranial neuronal source location, through the machine learning decoding of channel location.

Atherogenic lipoprotein profile associated with anthropometric indices of obesity and their association with cardiometabolic risk markers: a cross-sectional study in community

Background

Obesity, especially abdominal fat accumulation, is strongly associated with various metabolic comorbidities. Whether simple anthropometric measures are independently associated with atherogenic lipoproteins is not completely clear.

Methods

We randomly recruited 505 participants (51.5% women; mean age: 48.8 years) from the Flemish community, who had undergone lipoprotein particle measurements by nuclear magnetic resonance spectroscopy and conventional lipid measurements. Each lipoprotein fraction was subgrouped into large, medium, and small subclass. Anthropometric measures included body mass index (BMI) and waist-to-hip ratio (WHR), and defined BMI obesity as BMI ≥30 kg/m2, and WHR obesity as WHR ≥0.85 (women) or 0.9 (men).

Results

In the multivariable logistic regression analysis, total very-low-density lipoprotein (VLDL) particle and its subclasses were positively associated with BMI obesity (adjusted odds ratio [OR] for total VLDL: 2.37; 95% confidence interval [CI]: 1.70–3.31) and WHR obesity (OR for total VLDL: 2.06 [95% CI: 1.55–2.73]). The level of total high-density lipoprotein (HDL) particle and its subclass was negatively associated with BMI (OR for total HDL: 0.63 [95% CI: 0.45–0.90), but not with WHR (P≥0.11). None of the low-density lipoprotein (LDL) particles was associated with the two types of obesity (P≥0.092). BMI was inversely associated with the size of LDL and HDL particles, whereas high WHR was significantly associated with smaller VLDL and HDL sizes. For conventional lipid measures, both BMI and WHR were independently associated with high triglyceride and remnant cholesterol, both mainly driven from VLDL particles, and low HDL cholesterol (P≤0.008). These associations were confirmed in multivariable linear regression analysis, except the association of BMI with HDL number and the association of WHR with HDL size. With partial least squares analysis, the lipoprotein profiles of BMI and WHR were significantly associated with a high 10-year cardiovascular disease risk score, the homeostasis model assessment-estimated insulin resistance (HOMA-IR), and C-reactive protein.

Conclusion

BMI and WHR were independently associated with high triglyceride-rich lipoproteins, decreased HDL cholesterol. The size of LDL and HDL was more consistently associated with BMI than WHR. The lipoprotein alterations may link obesity with high cardiometabolic risk.

Funding Acknowledgement

Type of funding sources: Public grant(s) – EU funding. Main funding source(s): The European Research Council; the European Research Area Net for Cardiovascular Diseases

Association of fatal and non-fatal adverse health outcomes with urinary peptides reflecting collagen I turnover

Background

Imbalance of collagen I (COL1) turnover, featured by increased synthesis and decreased degradation of collagen fibers, is a hallmark of fibrosis in the heart and blood vessels that associates with poor cardiovascular outcomes. Such as imbalance of COL1 turnover could be reflected in urine and serve as fingerprint for future adverse outcomes in general population, and high risk subjects.

Purpose

We hypothesize that imbalance of proteomic signatures of urinary peptides (UPs) reflecting COL1 turnover relate to adverse health outcomes in participants from a general population

Methods

We randomly recruited 776 participants (51.2% women; 50.5 years) from the Flemish Study on Environment, Genes and Health Outcomes cohort and measured UPs proteome by capillary electrophoresis coupled with mass spectrometry. Our analyses focused on 148 peptides of COL1 alpha-1 (COL1A1) chain that retained ≥70% signal in the whole sample. The primary endpoint included fatal and nonfatal cardiovascular endpoints. Secondary endpoints consisted of total mortality, fatal and nonfatal cardiac, coronary, and heart failure endpoints. Multivariate Cox proportional models, partial least squares analysis (PLS), log-likelihood test, and receiver operating characteristics (ROC) curve were applied.

Results

Over a median follow up of 12.4 years, 110 primary endpoints occurred, 61 participants died, 81, 41 and 24 experienced cardiac, coronary, and heart failure endpoints; respectively. In PLS analyses, upregulation of UPs signatures closer to C- and N-terminal locations of the COL1A1 chain whereas downregulation of mid-region UPs were associated with lower risk of adverse health outcomes. This pattern was inverted in subjects with cardiovascular disease, as upregulation of terminal and downregulation of mid region UPs increased risk. Adding UPs to a basic model including sex, age and usual cardiovascular risk factors significantly improved model performance between 2.54% to 4.93% (P≤0.001) for prediction of adverse health outcomes. In ROC plots, adding UPs to the basic model increased the area under the curve up to 4.00% (P<0.012).

Conclusions

UPs reflecting COL1 turnover predicted adverse health outcomes. The inverted up- and down regulations of UPs in between participants with and without previous cardiovascular diseases might be explained by a shift in the UPs signatures of COL1 fragments linked to distinct fibrotic processes. Urinary proteomic might have clinical importance in documenting the extent of collagen accumulation that relates to adverse health outcomes. In patients at high cardiovascular risk, modification of collagen I fibers turnover might be a potential treatment target

Funding Acknowledgement

Type of funding sources: Public grant(s) – EU funding. Main funding source(s): The European Union the European Research Council and the European Research Area Net for Cardiovascular Diseases.

Scalable Biologically-Aware Skeleton Generation for Connectomic Volumes

As connectomic datasets exceed hundreds of terabytes in size, accurate and efficient skeleton generation of the label volumes has evolved into a critical component of the computation pipeline used for analysis, evaluation, visualization, and error correction. We propose a novel topological thinning strategy that uses biological-constraints to produce accurate centerlines from segmented neuronal volumes while still maintaining biologically relevant properties. Current methods are either agnostic to the underlying biology, have non-linear running times as a function of the number of input voxels, or both. First, we eliminate from the input segmentation biologically-infeasible bubbles, pockets of voxels incorrectly labeled within a neuron, to improve segmentation accuracy, allow for more accurate centerlines, and increase processing speed. Next, a Convolutional Neural Network (CNN) detects cell bodies from the input segmentation, allowing us to anchor our skeletons to the somata. Lastly, a synapse-aware topological thinning approach produces expressive skeletons for each neuron with a nearly one-to-one correspondence between endpoints and synapses. We simultaneously estimate geometric properties of neurite width and geodesic distance between synapse and cell body, improving accuracy by 47.5% and 62.8% over baseline methods. We separate the skeletonization process into a series of computation steps, leveraging data-parallel strategies to increase throughput significantly. We demonstrate our results on over 1250 neurons and neuron fragments from three different species, processing over one million voxels per second per CPU with linear scalability.

Review of Flexible Wearable Sensor Devices for Biomedical Application

With the development of cross-fertilisation in various disciplines, flexible wearable sensing technologies have emerged, bringing together many disciplines, such as biomedicine, materials science, control science, and communication technology. Over the past few years, the development of multiple types of flexible wearable devices that are widely used for the detection of human physiological signals has proven that flexible wearable devices have strong biocompatibility and a great potential for further development. These include electronic skin patches, soft robots, bio-batteries, and personalised medical devices. In this review, we present an updated overview of emerging flexible wearable sensor devices for biomedical applications and a comprehensive summary of the research progress and potential of flexible sensors. First, we describe the selection and fabrication of flexible materials and their excellent electrochemical properties. We evaluate the mechanisms by which these sensor devices work, and then we categorise and compare the unique advantages of a variety of sensor devices from the perspective of in vitro and in vivo sensing, as well as some exciting applications in the human body. Finally, we summarise the opportunities and challenges in the field of flexible wearable devices.

[Prolonged epidural labor analgesia increases risks of epidural analgesia failure for conversion to cesarean section]

OBJECTIVE

To explore the effect of epidural labor analgesia duration on the outcomes of different anesthetic approaches for conversion to cesarean section.

METHODS

We retrospectively collected the clinical data of pregnant women undergoing conversion from epidural labor analgesia to cesarean section at Sichuan Maternal and Child Health Hospital and Jinjiang District Maternal and Child Health Care Hospital between July, 2019 and June, 2020. For cesarean section, the women received epidural anesthesia when the epidural catheter was maintained in correct position with effective analgesia, spinal anesthesia at the discretion of the anesthesiologists, or general anesthesia in cases requiring immediate cesarean section or following failure of epidural anesthesia or spinal anesthesia. Receiver-operating characteristic curve analysis was performed to determine the cutoff value of the analgesia duration using Youden index. The women were divided into two groups according to the cut off value for analyzing the relative risk using cross tabulations.

RESULTS

A total of 820 pregnant women undergoing conversion to cesarean section were enrolled in this analysis, including 615 (75.0%) in epidural anesthesia group, 186 (22.7%) in spinal anesthesia group, and 19 (2.3%) in general anesthesia group; none of the women experienced failure of epidural or spinal anesthesia. The mean anesthesia duration was 8.2±4.7 h in epidural anesthesia, 10.6±5.1 h in spinal anesthesia group, and 6.7 ± 5.2 h in general anesthesia group. Multivariate logistic regression analysis showed that prolongation of analgesia duration by 1 h (OR=1.094, 95% CI: 1.057-1.132, P < 0.001) and an increase of cervical orifice by 1 cm (OR=1.066, 95% CI: 1.011-1.124, P=0.017) were independent risk factors for epidural analgesia failure. The cutoff value of analgesia duration was 9.5 h, and beyond that duration the relative risk of receiving spinal anesthesia was 1.204 (95% CI: 1.103-2.341, P < 0.001).

CONCLUSION

Prolonged epidural labor analgesia increases the risk of failure of epidural analgesia for conversion to epidural anesthesia. In cases with an analgesia duration over 9.5 h, spinal anesthesia is recommended if immediate cesarean section is not required.