Improving Triethylamine-Sensing Performance of WO3 Nanoplates through In Situ Heterojunction Construction.

Surface engineering techniques can be used to develop high-performance gas sensing materials and advance the development of sensors. In this study, we improved the gas sensing performance of two-dimensional (2D) WO3 nanoplates by combining surface Zn modification and the in situ formation of ZnWO4/WO3 heterojunctions. Introducing Zn atoms by surface modification can reconstruct the atomic surface of 2D WO3 nanoplates, creating additional active sites. This allowed for the preparation of various types of ZnWO4/WO3 heterojunctions on the surface of the WO3 nanoplates, which improved the selectivity and sensitivity to the target gas triethylamine. The sensor exhibited good gas sensing performance for triethylamine even at low operating temperatures and strongly resisted humidity changes. The ZnWO4/WO3 material we prepared demonstrated a nearly threefold improvement in the triethylamine (TEA) response, with a gas sensing responsivity of 40.75 for 10 ppm of TEA at 250 °C. The sensor based on ZnWO4/WO3 has a limit of detection (LOD) for TEA of 200 ppb in practical measurements (its theoretical LOD is even as low as 31 ppb). The method of growing ZnWO4 on the surface of WO3 nanoplates using surface modification techniques to form surface heterojunctions differs from ordinary composites. The results suggest that the in situ construction of surface heterojunctions using surface engineering strategies, such as in situ modifying, is a practical approach to enhance the gas sensing properties and resistance to the humidity changes of metal oxide materials.

Enhancing Rapid Li+/Na+ Storage Performance via Interface Engineering of Reduced Graphene Oxide-Wrapped Bimetallic Sulfide Nanocages.

Transition-metal sulfide is considered to be an admirable transformational electrode material due to low cost, large specific capacity, and good reversibility in lithium-ion batteries (LIBs) and sodium-ion batteries (SIBs). Herein, the reduced graphene oxide-wrapped open bimetallic sulfide (NiS2-Co3S4@rGO) nanocage, derived from nickel-cobalt Prussian blue, was obtained by two-step calcination. There are luxuriant pore structures in the nanocage composite with a specific surface area of 85.28 m2 g-1, which provides plentiful paths for rapid transmission of Li+/Na+ and alleviates the volume stress caused by insertion and extraction of alkali metal ions. The excellent interface combination of bimetallic sulfide wrapped in reduced graphene oxide improves the conductivity and overall performance of the battery. Thanks to the special interface engineering, the open NiS2-Co3S4@rGO nanocage composite displays rapid lithium storage properties with an average diffusion coefficient of 8.5 × 10-13 cm2 s-1. Moreover, after 300 cycles, the reversible capacity of the composite is 1113.2 mAh g-1 at 1 A g-1. In SIBs, the capacity of the open NiS2-Co3S4@rGO composite is 487.9 mAh g-1 when the current density is 5 A g-1. These preeminent performances demonstrate the enormous development prospects of bimetallic sulfide nanocage as anode material in LIBs and SIBs.

In Situ Synthesis of Hierarchical Co(CO3)0.5(OH)·0.11H2O@ZIF-67/WO3 With High Humidity Immunity and Response to H2S Sensing.

H2S gas sensors with facile preparation, low detection limits, and high selectivity are crucial for environmental and human health monitoring. However, it is difficult to maintain a high response of H2S gas sensors under high humidity in practical applications. To face this dilemma, a layer-by-layer growth method is applied to in situ prepare a nanostructured Co(CO3)0.5(OH)·0.11H2O/WO3 coated by a hydrophobic hierarchical ZIF-67 as the H2S sensor. This novel composite exhibits excellent humidity immunity without sacrificing the excellent sensitivity and selectivity of H2S. At a low operating temperature of 90 °C, a remarkable response value of 1052.3 to 100 ppm H2S has been achieved, which is 779 and 9.36 times higher than that of pure WO3 and Co(CO3)0.5(OH)·0.11H2O/WO3, respectively. More importantly, an 82.2% relative response value remains at a high humidity of 75%RH. The sensing mechanisms are investigated using gas chromatography-mass spectrometry (GC-MS), which revealed that the reaction products are H2O and SO2. The high humidity immunity and fast response of the Co(CO3)0.5(OH)·0.11H2O@ZIF-67/WO3 demonstrate the layer-by-layer in situ synthesis method holds the potential application for the development of high-performance WO3-based H2S sensors.

TMV-CP based rational design and discovery of α-Amide phosphate derivatives as anti plant viral agents.

The tobacco mosaic virus coat protein (TMV-CP) is indispensable for the virus's replication, movement and transmission, as well as for the host plant's immune system to recognize it. It constitutes the outermost layer of the virus particle, and serves as an essential component of the virus structure. TMV-CP is essential for initiating and extending viral assembly, playing a crucial role in the self-assembly process of Tobacco Mosaic Virus (TMV). This research employed TMV-CP as a primary target for virtual screening, from which a library of 43,417 compounds was sourced and SH-05 was chosen as the lead compound. Consequently, a series of α-amide phosphate derivatives were designed and synthesized, exhibiting remarkable anti-TMV efficacy. The synthesized compounds were found to be beneficial in treating TMV, with compound 3g displaying a slightly better curative effect than Ningnanmycin (NNM) (EC50 = 304.54 µg/mL) at an EC50 of 291.9 µg/mL. Additionally, 3g exhibited comparable inactivation activity (EC50 = 63.2 µg/mL) to NNM (EC50 = 67.5 µg/mL) and similar protective activity (EC50 = 228.9 µg/mL) to NNM (EC50 = 219.7 µg/mL). Microscale thermal analysis revealed that the binding of 3g (Kd = 4.5 ± 1.9 µM) to TMV-CP showed the same level with NNM (Kd = 5.5 ± 2.6 µM). Results from transmission electron microscopy indicated that 3g could disrupt the structure of TMV virus particles. The toxicity prediction indicated that 3g was low toxicity. Molecular docking showed that 3g interacted with TMV-CP through hydrogen bond, attractive charge interaction and π-Cation interaction. This research provided a novel α-amide phosphate structure target TMV-CP, which may help the discovery of new anti-TMV agents in the future.

Three-degrees-of-freedom orientation manipulation of small untethered robots with a single anisotropic soft magnet.

Magnetic actuation has been well exploited for untethered manipulation and locomotion of small-scale robots in complex environments such as intracorporeal lumens. Most existing magnetic actuation systems employ a permanent magnet onboard the robot. However, only 2-DoF orientation of the permanent-magnet robot can be controlled since no torque can be generated about its axis of magnetic moment, which limits the dexterity of manipulation. Here, we propose a new magnetic actuation method using a single soft magnet with an anisotropic geometry (e.g., triaxial ellipsoids) for full 3-DoF orientation manipulation. The fundamental actuation principle of anisotropic magnetization and 3-DoF torque generation are analytically modeled and experimentally validated. The hierarchical orientation stability about three principal axes is investigated, based on which we propose and validate a multi-step open-loop control strategy to alternatingly manipulate the direction of the longest axis of the soft magnet and the rotation about it for dexterous 3-DoF orientation manipulation.

Resolving the lineage relationship between malignant cells and vascular cells in glioblastomas.

Glioblastoma multiforme (GBM), a highly malignant and heterogeneous brain tumor, contains various types of tumor and non-tumor cells. Whether GBM cells can trans-differentiate into non-neural cell types, including mural cells or endothelial cells (ECs), to support tumor growth and invasion remains controversial. Here we generated two genetic GBM models de novo in immunocompetent mouse brains, mimicking essential pathological and molecular features of human GBMs. Lineage-tracing and transplantation studies demonstrated that, although blood vessels in GBM brains underwent drastic remodeling, evidence of trans-differentiation of GBM cells into vascular cells was barely detected. Intriguingly, GBM cells could promiscuously express markers for mural cells during gliomagenesis. Furthermore, single-cell RNA sequencing showed that patterns of copy number variations (CNVs) of mural cells and ECs were distinct from those of GBM cells, indicating discrete origins of GBM cells and vascular components. Importantly, single-cell CNV analysis of human GBM specimens also suggested that GBM cells and vascular cells are likely separate lineages. Rather than expansion owing to trans-differentiation, vascular cell expanded by proliferation during tumorigenesis. Therefore, cross-lineage trans-differentiation of GBM cells is very unlikely to occur during gliomagenesis. Our findings advance understanding of cell lineage dynamics during gliomagenesis, and have implications for targeted treatment of GBMs.

A Ctnnb1 enhancer regulates neocortical neurogenesis by controlling the abundance of intermediate progenitors.

ß-catenin-dependent canonical Wnt signaling plays a plethora of roles in neocortex (Ncx) development, but its function in regulating the abundance of intermediate progenitors (IPs) is elusive. Here we identified neCtnnb1, an evolutionarily conserved cis-regulatory element with typical enhancer features in developing Ncx. neCtnnb1 locates 55 kilobase upstream of and spatially close to the promoter of Ctnnb1, the gene encoding ß-catenin. CRISPR/Cas9-mediated activation or interference of the neCtnnb1 locus enhanced or inhibited transcription of Ctnnb1. neCtnnb1 drove transcription predominantly in the subventricular zone of developing Ncx. Knock-out of neCtnnb1 in mice resulted in compromised expression of Ctnnb1 and the Wnt reporter in developing Ncx. Importantly, knock-out of neCtnnb1 lead to reduced production and transit-amplification of IPs, which subsequently generated fewer upper-layer Ncx projection neurons (PNs). In contrast, enhancing the canonical Wnt signaling by stabilizing ß-catenin in neCtnnb1-active cells promoted the production of IPs and upper-layer Ncx PNs. ASH2L was identified as the key trans-acting factor that associates with neCtnnb1 and Ctnnb1's promoter to maintain Ctnnb1's transcription in both mouse and human Ncx progenitors. These findings advance understanding of transcriptional regulation of Ctnnb1, and provide insights into mechanisms underlying Ncx expansion during development.

Influence of Drought Stress and Post-Drought Rewatering on Phytoremediation Effect of Arabidopsis thaliana.

Globally, plants face large amounts of environmental stresses, which can inhibit their growth rate and element uptake capacity. Droughts are a critical limitation to plant growth in arid and semi-arid areas. Effects of drought stress and post-drought rewatering on the compensatory growth and Cd phytoremediation efficiency of Arabidopsis thaliana were estimated using slight and moderate drought conditions. Results showed compensatory growth can be induced by post-drought rewatering, as manifested by the increased dry weight and photosynthetic efficiency of the species under drought stress (particularly slight stress) as compared to those of the control. Slight stress increased concentrations of Cd in roots and leaves of A. thaliana by elevating its transpiration rate, whereas moderate stress induced the opposite effect. When the species was subjected to slight stress, Cd concentrations in plant tissues surpassed those in the control after rewatering, indicating that post-drought rewatering can compensate for the detrimental impacts caused by slight drought in A. thaliana. At the end of the experiment, slight and moderate drought stresses increased the Cd extraction ability of the species by 48.9% and 12.7%, respectively, compared to the control. This study demonstrates compensatory effects of post-drought rewatering on the Cd phytoextraction capacity of A. thaliana and suggests that suitable water deficit irrigation practices can enhance soil remediation efficiency and simultaneously save water in the field.

Joint fully convolutional and graph convolutional networks for weakly-supervised segmentation of pathology images.

Tissue/region segmentation of pathology images is essential for quantitative analysis in digital pathology. Previous studies usually require full supervision (e.g., pixel-level annotation) which is challenging to acquire. In this paper, we propose a weakly-supervised model using joint Fully convolutional and Graph convolutional Networks (FGNet) for automated segmentation of pathology images. Instead of using pixel-wise annotations as supervision, we employ an image-level label (i.e., foreground proportion) as weakly-supervised information for training a unified convolutional model. Our FGNet consists of a feature extraction module (with a fully convolutional network) and a classification module (with a graph convolutional network). These two modules are connected via a dynamic superpixel operation, making the joint training possible. To achieve robust segmentation performance, we propose to use mutable numbers of superpixels for both training and inference. Besides, to achieve strict supervision, we employ an uncertainty range constraint in FGNet to reduce the negative effect of inaccurate image-level annotations. Compared with fully-supervised methods, the proposed FGNet achieves competitive segmentation results on three pathology image datasets (i.e., HER2, KI67, and H&E) for cancer region segmentation, suggesting the effectiveness of our method. The code is made publicly available at https://github.com/zhangjun001/FGNet.

Can AI-assisted microscope facilitate breast HER2 interpretation? A multi-institutional ring study.

The level of human epidermal growth factor receptor-2 (HER2) protein and gene expression in breast cancer is an essential factor in judging the prognosis of breast cancer patients. Several investigations have shown high intraobserver and interobserver variability in the evaluation of HER2 staining by visual examination. In this study, we aim to propose an artificial intelligence (AI)-assisted microscope to improve the HER2 assessment accuracy and reliability. Our AI-assisted microscope was equipped with a conventional microscope with a cell-level classification-based HER2 scoring algorithm and an augmented reality module to enable pathologists to obtain AI results in real time. We organized a three-round ring study of 50 infiltrating duct carcinoma not otherwise specified (NOS) cases without neoadjuvant treatment, and recruited 33 pathologists from 6 hospitals. In the first ring study (RS1), the pathologists read 50 HER2 whole-slide images (WSIs) through an online system. After a 2-week washout period, they read the HER2 slides using a conventional microscope in RS2. After another 2-week washout period, the pathologists used our AI microscope for assisted interpretation in RS3. The consistency and accuracy of HER2 assessment by the AI-assisted microscope were significantly improved (p < 0.001) over those obtained using a conventional microscope and online WSI. Specifically, our AI-assisted microscope improved the precision of immunohistochemistry (IHC) 3 + and 2 + scoring while ensuring the recall of fluorescent in situ hybridization (FISH)-positive results in IHC 2 + . Also, the average acceptance rate of AI for all pathologists was 0.90, demonstrating that the pathologists agreed with most AI scoring results.

How can artificial intelligence models assist PD-L1 expression scoring in breast cancer: results of multi-institutional ring studies.

Programmed death ligand-1 (PD-L1) expression is a key biomarker to screen patients for PD-1/PD-L1-targeted immunotherapy. However, a subjective assessment guide on PD-L1 expression of tumor-infiltrating immune cells (IC) scoring is currently adopted in clinical practice with low concordance. Therefore, a repeatable and quantifiable PD-L1 IC scoring method of breast cancer is desirable. In this study, we propose a deep learning-based artificial intelligence-assisted (AI-assisted) model for PD-L1 IC scoring. Three rounds of ring studies (RSs) involving 31 pathologists from 10 hospitals were carried out, using the current guideline in the first two rounds (RS1, RS2) and our AI scoring model in the last round (RS3). A total of 109 PD-L1 (Ventana SP142) immunohistochemistry (IHC) stained images were assessed and the role of the AI-assisted model was evaluated. With the assistance of AI, the scoring concordance across pathologists was boosted to excellent in RS3 (0.950, 95% confidence interval (CI): 0.936-0.962) from moderate in RS1 (0.674, 95% CI: 0.614-0.735) and RS2 (0.736, 95% CI: 0.683-0.789). The 2- and 4-category scoring accuracy were improved by 4.2% (0.959, 95% CI: 0.953-0.964) and 13% (0.815, 95% CI: 0.803-0.827) (p < 0.001). The AI results were generally accepted by pathologists with 61% "fully accepted" and 91% "almost accepted". The proposed AI-assisted method can help pathologists at all levels to improve the PD-L1 assay (SP-142) IC assessment in breast cancer in terms of both accuracy and concordance. The AI tool provides a scheme to standardize the PD-L1 IC scoring in clinical practice.

Metformin Inhibits the Urea Cycle and Reduces Putrescine Generation in Colorectal Cancer Cell Lines.

The urea cycle (UC) removes the excess nitrogen and ammonia generated by nitrogen-containing compound composites or protein breakdown in the human body. Research has shown that changes in UC enzymes are not only related to tumorigenesis and tumor development but also associated with poor survival in hepatocellular, breast, and colorectal cancers (CRC), etc. Cytoplasmic ornithine, the intermediate product of the urea cycle, is a specific substrate for ornithine decarboxylase (ODC, also known as ODC1) for the production of putrescine and is required for tumor growth. Polyamines (spermidine, spermine, and their precursor putrescine) play central roles in more than half of the steps of colorectal tumorigenesis. Given the close connection between polyamines and cancer, the regulation of polyamine metabolic pathways has attracted attention regarding the mechanisms of action of chemical drugs used to prevent CRC, as the drug most widely used for treating type 2 diabetes (T2D), metformin (Met) exhibits antitumor activity against a variety of cancer cells, with a vaguely defined mechanism. In addition, the influence of metformin on the UC and putrescine generation in colorectal cancer has remained unclear. In our study, we investigated the effect of metformin on the UC and putrescine generation of CRC in vivo and in vitro and elucidated the underlying mechanisms. In nude mice bearing HCT116 tumor xenografts, the administration of metformin inhibited tumor growth without affecting body weight. In addition, metformin treatment increased the expression of monophosphate (AMP)-activated protein kinase (AMPK) and p53 in both HCT116 xenografts and colorectal cancer cell lines and decreased the expression of the urea cycle enzymes, including carbamoyl phosphate synthase 1 (CPS1), arginase 1 (ARG1), ornithine trans-carbamylase (OTC), and ODC. The putrescine levels in both HCT116 xenografts and HCT116 cells decreased after metformin treatment. These results demonstrate that metformin inhibited CRC cell proliferation via activating AMPK/p53 and that there was an association between metformin, urea cycle inhibition and a reduction in putrescine generation.

Improving Ki67 assessment concordance by the use of an artificial intelligence-empowered microscope: a multi-institutional ring study.

AIMS: The nuclear proliferation biomarker Ki67 plays potential prognostic and predictive roles in breast cancer treatment. However, the lack of interpathologist consistency in Ki67 assessment limits the clinical use of Ki67. The aim of this article was to report a solution utilising an artificial intelligence (AI)-empowered microscope to improve Ki67 scoring concordance. METHODS AND RESULTS: We developed an AI-empowered microscope in which the conventional microscope was equipped with AI algorithms, and AI results were provided to pathologists in real time through augmented reality. We recruited 30 pathologists with various experience levels from five institutes to assess the Ki67 labelling index on 100 Ki67-stained slides from invasive breast cancer patients. In the first round, pathologists conducted visual assessment on a conventional microscope; in the second round, they were assisted with reference cards; and in the third round, they were assisted with an AI-empowered microscope. Experienced pathologists had better reproducibility and accuracy [intraclass correlation coefficient (ICC) = 0.864, mean error = 8.25%] than inexperienced pathologists (ICC = 0.807, mean error = 11.0%) in visual assessment. Moreover, with reference cards, inexperienced pathologists (ICC = 0.836, mean error = 10.7%) and experienced pathologists (ICC = 0.875, mean error = 7.56%) improved their reproducibility and accuracy. Finally, both experienced pathologists (ICC = 0.937, mean error = 4.36%) and inexperienced pathologists (ICC = 0.923, mean error = 4.71%) improved the reproducibility and accuracy significantly with the AI-empowered microscope. CONCLUSION: The AI-empowered microscope allows seamless integration of the AI solution into the clinical workflow, and helps pathologists to obtain higher consistency and accuracy for Ki67 assessment.

An epigenetic circuit controls neurogenic programs during neocortex development.

The production and expansion of intermediate progenitors (IPs) are essential for neocortical neurogenesis during development and over evolution. Here, we have characterized an epigenetic circuit that precisely controls neurogenic programs, particularly properties of IPs, during neocortical development. The circuit comprises a long non-coding RNA (LncBAR) and the BAF (SWI/SNF) chromatin-remodeling complex, which transcriptionally maintains the expression of Zbtb20. LncBAR knockout neocortex contains more deep-layer but fewer upper-layer projection neurons. Intriguingly, loss of LncBAR promotes IP production, but paradoxically prolongs the duration of the cell cycle of IPs during mid-later neocortical neurogenesis. Moreover, in LncBAR knockout mice, depletion of the neural progenitor pool at embryonic stage results in fewer adult neural progenitor cells in the subventricular zone of lateral ventricles, leading to a failure in adult neurogenesis to replenish the olfactory bulb. LncBAR binds to BRG1, the core enzymatic component of the BAF chromatin-remodeling complex. LncBAR depletion enhances association of BRG1 with the genomic locus of, and suppresses the expression of, Zbtb20, a transcription factor gene known to regulate both embryonic and adult neurogenesis. ZBTB20 overexpression in LncBAR-knockout neural precursors reverses compromised cell cycle progressions of IPs.

Transcriptome Analysis Identifies SenZfp536, a Sense LncRNA that Suppresses Self-renewal of Cortical Neural Progenitors.

Long non-coding RNAs (lncRNAs) regulate transcription to control development and homeostasis in a variety of tissues and organs. However, their roles in the development of the cerebral cortex have not been well elucidated. Here, a bioinformatics pipeline was applied to delineate the dynamic expression and potential cis-regulating effects of mouse lncRNAs using transcriptome data from 8 embryonic time points and sub-regions of the developing cerebral cortex. We further characterized a sense lncRNA, SenZfp536, which is transcribed downstream of and partially overlaps with the protein-coding gene Zfp536. Both SenZfp536 and Zfp536 were predominantly expressed in the proliferative zone of the developing cortex. Zfp536 was cis-regulated by SenZfp536, which facilitates looping between the promoter of Zfp536 and the genomic region that transcribes SenZfp536. Surprisingly, knocking down or activating the expression of SenZfp536 increased or compromised the proliferation of cortical neural progenitor cells (NPCs), respectively. Finally, overexpressing Zfp536 in cortical NPCs reversed the enhanced proliferation of cortical NPCs caused by SenZfp536 knockdown. The study deepens our understanding of how lncRNAs regulate the propagation of cortical NPCs through cis-regulatory mechanisms.

Inhibition of Endoplasmic Reticulum Stress-Mediated Autophagy Enhances the Anticancer Effect of Iodine-125 Seed Radiation on Esophageal Squamous Cell Carcinoma.

Autophagy has been reported to play a radioresistance role in high-dose-rate irradiation. However, its mechanisms and roles in continuous low-dose-rate (CLDR) irradiation have not been clearly understood. Iodine-125 (I-125) seed brachytherapy is a modality of CLDR irradiation and has been used in the treatment of various cancers. In this study, we investigated the mechanisms and roles of autophagy induced by I-125 seed radiation in human esophageal squamous cell carcinoma (ESCC) cell lines (Eca-109 and EC-109) and a xenograft mouse model. The results of this work showed that I-125 seed radiation induced a dose-dependent increase in autophagy in both cell lines. In Eca-109 cells, I-125 seed radiation-induced endoplasmic reticulum (ER) stress, manifesting as the increased levels of intracellular Ca2+ and Grp78/BiP, and activated PERK-eIF2α, IRE1, and ATF6 pathways of the unfolded protein response. Knockdown of PERK led to the decreased expression of autophagy marker, LC3B-II. Inhibition of autophagy by chloroquine or knockdown of ATG5 enhanced I-125 seed radiation-induced cell proliferation inhibition and apoptosis. Interestingly, chloroquine did not aggravate ER stress but promoted apoptosis via the mitochondrial pathway. The animal experiment showed that inhibition of autophagy by chloroquine improved the efficacy of I-125 seed radiation. In summary, our data demonstrate that I-125 seed CLDR radiation induces ER stress-mediated autophagy in ESCC. Autophagy plays a pro-survival role in I-125 seed CLDR irradiation, and chloroquine is a potential candidate for use in combination therapy with I-125 seed radiation treatment to improve efficacy against ESCC.

Iodine­125 seed radiation induces ROS­mediated apoptosis, autophagy and paraptosis in human esophageal squamous cell carcinoma cells.

Iodine­125 (125I) seed brachytherapy has been proven to be a safe and effective treatment for advanced esophageal cancer; however, the mechanisms underlying its actions are not completely understood. In the present study, the anti­cancer mechanisms of 125I seed radiation in human esophageal squamous cell carcinoma (ESCC) cells (Eca­109 and KYSE­150) were determined, with a particular focus on the mode of cell death. The results showed that 125I seed radiation significantly inhibited cell proliferation, and induced DNA damage and G2/M cell cycle arrest in both ESCC cell lines. 125I seed radiation induced cell death through both apoptosis and paraptosis. Eca­109 cells were primarily killed by inducing caspase­dependent apoptosis, with 6 Gy radiation resulting in the largest response. KYSE­150 cells were primarily killed by inducing paraptosis, which is characterized by extensive cytoplasmic vacuolation. 125I seed radiation induced autophagic flux in both ESCC cell lines, and autophagy inhibition by 3­methyladenine enhanced radiosensitivity. Furthermore 125I seed radiation induced increased production of reactive oxygen species (ROS) in both ESCC cell lines. Treatment with an ROS scavenger significantly attenuated the effects of 125I seed radiation on endoplasmic reticulum stress, autophagy, apoptosis, paraptotic vacuoles and reduced cell viability. In vivo experiments showed that 125I seed brachytherapy induced ROS generation, initiated cell apoptosis and potential paraptosis, and inhibited cell proliferation and tumor growth. In summary, the results demonstrate that in ESCC cells, 125I seed radiation induces cell death through both apoptosis and paraptosis; and at the same time initiates protective autophagy. Additionally, 125I seed radiation­induced apoptosis, paraptosis and autophagy was considerably mediated by ROS.

Long non-coding RNA LncKdm2b regulates cortical neuronal differentiation by cis-activating Kdm2b.

The mechanisms underlying spatial and temporal control of cortical neurogenesis of the brain are largely elusive. Long non-coding RNAs (lncRNAs) have emerged as essential cell fate regulators. Here we found LncKdm2b (also known as Kancr), a lncRNA divergently transcribed from a bidirectional promoter of Kdm2b, is transiently expressed during early differentiation of cortical projection neurons. Interestingly, Kdm2b's transcription is positively regulated in cis by LncKdm2b, which has intrinsic-activating function and facilitates a permissive chromatin environment at the Kdm2b's promoter by associating with hnRNPAB. Lineage tracing experiments and phenotypic analyses indicated LncKdm2b and Kdm2b are crucial in proper differentiation and migration of cortical projection neurons. These observations unveiled a lncRNA-dependent machinery in regulating cortical neuronal differentiation.

Multicontext multitask learning networks for mass detection in mammogram.

PURPOSE: In this paper, for the purpose of accurate and efficient mass detection, we propose a new deep learning framework, including two major stages: Suspicious region localization (SRL) and Multicontext Multitask Learning (MCMTL). METHODS: In the first stage, SRL focuses on finding suspicious regions [regions of interest (ROIs)] and extracting multisize patches of these suspicious regions. A set of bounding boxes with different size is used to extract multisize patches, which aim to capture diverse context information. In the second stage, MCMTL networks integrate features from multisize patches of suspicious regions for classification and segmentation simultaneously, where the purpose of this stage is to keep the true positive suspicious regions and to reduce the false positive suspicious regions. RESULTS: According to the experimental results on two public datasets (i.e., CBIS-DDSM and INBreast), our method achieves the overall performance of 0.812 TPR@2.53 FPI and 0.919 TPR@0.12 FPI on test sets, respectively. CONCLUSIONS: Our proposed method suggests comparable performance to the state-of-the-art methods.

High urea induces depression and LTP impairment through mTOR signalling suppression caused by carbamylation.

BACKGROUND: Urea, the end product of protein metabolism, has been considered to have negligible toxicity for a long time. Our previous study showed a depression phenotype in urea transporter (UT) B knockout mice, which suggests that abnormal urea metabolism may cause depression. The purpose of this study was to determine if urea accumulation in brain is a key factor causing depression using clinical data and animal models. METHODS: A meta-analysis was used to identify the relationship between depression and chronic diseases. Functional Magnetic Resonance Imaging (fMRI) brain scans and common biochemical indexes were compared between the patients and healthy controls. We used behavioural tests, electrophysiology, and molecular profiling techniques to investigate the functional role and molecular basis in mouse models. FINDINGS: After performing a meta-analysis, we targeted the relevance between chronic kidney disease (CKD) and depression. In a CKD mouse model and a patient cohort, depression was induced by impairing the medial prefrontal cortex. The enlarged cohort suggested that urea was responsible for depression. In mice, urea was sufficient to induce depression, interrupt long-term potentiation (LTP) and cause loss of synapses in several models. The mTORC1-S6K pathway inhibition was necessary for the effect of urea. Lastly, we identified that the hydrolysate of urea, cyanate, was also involved in this pathophysiology. INTERPRETATION: These data indicate that urea accumulation in brain is an independent factor causing depression, bypassing the psychosocial stress. Urea or cyanate carbamylates mTOR to inhibit the mTORC1-S6K dependent dendritic protein synthesis, inducing impairment of synaptic plasticity in mPFC and depression-like behaviour. CKD patients may be able to attenuate depression only by strict management of blood urea.