Visualizing Intracellular Organelle and Cytoskeletal Interactions at Nanoscale Resolution on Millisecond Timescales.

In eukaryotic cells, organelles and the cytoskeleton undergo highly dynamic yet organized interactions capable of orchestrating complex cellular functions. Visualizing these interactions requires noninvasive, long-duration imaging of the intracellular environment at high spatiotemporal resolution and low background. To achieve these normally opposing goals, we developed grazing incidence structured illumination microscopy (GI-SIM) that is capable of imaging dynamic events near the basal cell cortex at 97-nm resolution and 266 frames/s over thousands of time points. We employed multi-color GI-SIM to characterize the fast dynamic interactions of diverse organelles and the cytoskeleton, shedding new light on the complex behaviors of these structures. Precise measurements of microtubule growth or shrinkage events helped distinguish among models of microtubule dynamic instability. Analysis of endoplasmic reticulum (ER) interactions with other organelles or microtubules uncovered new ER remodeling mechanisms, such as hitchhiking of the ER on motile organelles. Finally, ER-mitochondria contact sites were found to promote both mitochondrial fission and fusion.

A computational framework of routine test data for the cost-effective chronic disease prediction.

Chronic diseases, because of insidious onset and long latent period, have become the major global disease burden. However, the current chronic disease diagnosis methods based on genetic markers or imaging analysis are challenging to promote completely due to high costs and cannot reach universality and popularization. This study analyzed massive data from routine blood and biochemical test of 32 448 patients and developed a novel framework for cost-effective chronic disease prediction with high accuracy (AUC 87.32%). Based on the best-performing XGBoost algorithm, 20 classification models were further constructed for 17 types of chronic diseases, including 9 types of cancers, 5 types of cardiovascular diseases and 3 types of mental illness. The highest accuracy of the model was 90.13% for cardia cancer, and the lowest was 76.38% for rectal cancer. The model interpretation with the SHAP algorithm showed that CREA, R-CV, GLU and NEUT% might be important indices to identify the most chronic diseases. PDW and R-CV are also discovered to be crucial indices in classifying the three types of chronic diseases (cardiovascular disease, cancer and mental illness). In addition, R-CV has a higher specificity for cancer, ALP for cardiovascular disease and GLU for mental illness. The association between chronic diseases was further revealed. At last, we build a user-friendly explainable machine-learning-based clinical decision support system (DisPioneer: http://bioinfor.imu.edu.cn/dispioneer) to assist in predicting, classifying and treating chronic diseases. This cost-effective work with simple blood tests will benefit more people and motivate clinical implementation and further investigation of chronic diseases prevention and surveillance program.

Disease trend analysis platform accurately predicts the occurrence of cervical cancer under mixed diseases.

Cervical cancer (CC) is one of the most common gynecological malignancies. Cytological screening, while being the most common and accurate method for detecting cervical cancer, is both time-consuming and costly. Predicting CC based on bioinformatics can assist in the rapid early screening of CC in clinical practice. Most recent CC prediction methods require a large amount of detection data or sequencing data and are not ideal for CC detection in complex disease samples. We developed the Disease trend analysis platform (Dtap), which can quickly predict the occurrence of diseases using only blood routine data. Blood routine data was collected from 1,292 cervical cancer patients, 4,860 patients with complex diseases, and 4,980 healthy individuals from various sources. The results show that the Dtap-based trend model maintained good and stable performance in the prediction task of multiple datasets as well as complex disease samples. Finally, we built DTAPCC (http://bioinfor.imu.edu.cn/dtapcc), a Dtap-based CC disease prediction platform, to help users quickly predict CC and visualize trend features.

Self-construction of actin networks through phase separation-induced abLIM1 condensates.

The abLIM1 is a nonerythroid actin-binding protein critical for stable plasma membrane-cortex interactions under mechanical tension. Its depletion by RNA interference results in sparse, poorly interconnected cortical actin networks and severe blebbing of migrating cells. Its isoforms, abLIM-L, abLIM-M, and abLIM-S, contain, respectively four, three, and no LIM domains, followed by a C terminus entirely homologous to erythroid cortex protein dematin. How abLIM1 functions, however, remains unclear. Here we show that abLIM1 is a liquid-liquid phase separation (LLPS)-dependent self-organizer of actin networks. Phase-separated condensates of abLIM-S-mimicking ΔLIM or the major isoform abLIM-M nucleated, flew along, and cross-linked together actin filaments (F-actin) to produce unique aster-like radial arrays and interconnected webs of F-actin bundles. Interestingly, ΔLIM condensates facilitated actin nucleation and network formation even in the absence of Mg2+. Our results suggest that abLIM1 functions as an LLPS-dependent actin nucleator and cross-linker and provide insights into how LLPS-induced condensates could self-construct intracellular architectures of high connectivity and plasticity.

Altered intersubject functional variability of brain white-matter in major depressive disorder and its association with gene expression profiles.

Major depressive disorder (MDD) is a clinically heterogeneous disorder. Its mechanism is still unknown. Although the altered intersubject variability in functional connectivity (IVFC) within gray-matter has been reported in MDD, the alterations to IVFC within white-matter (WM-IVFC) remain unknown. Based on the resting-state functional MRI data of discovery (145 MDD patients and 119 healthy controls [HCs]) and validation cohorts (54 MDD patients, and 78 HCs), we compared the WM-IVFC between the two groups. We further assessed the meta-analytic cognitive functions related to the alterations. The discriminant WM-IVFC values were used to classify MDD patients and predict clinical symptoms in patients. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging association analyses were further conducted to investigate gene expression profiles associated with WM-IVFC alterations in MDD, followed by a set of gene functional characteristic analyses. We found extensive WM-IVFC alterations in MDD compared to HCs, which were associated with multiple behavioral domains, including sensorimotor processes and higher-order functions. The discriminant WM-IVFC could not only effectively distinguish MDD patients from HCs with an area under curve ranging from 0.889 to 0.901 across three classifiers, but significantly predict depression severity (r = 0.575, p = 0.002) and suicide risk (r = 0.384, p = 0.040) in patients. Furthermore, the variability-related genes were enriched for synapse, neuronal system, and ion channel, and predominantly expressed in excitatory and inhibitory neurons. Our results obtained good reproducibility in the validation cohort. These findings revealed intersubject functional variability changes of brain WM in MDD and its linkage with gene expression profiles, providing potential implications for understanding the high clinical heterogeneity of MDD.

Evaluation and development of deep neural networks for image super-resolution in optical microscopy.

Deep neural networks have enabled astonishing transformations from low-resolution (LR) to super-resolved images. However, whether, and under what imaging conditions, such deep-learning models outperform super-resolution (SR) microscopy is poorly explored. Here, using multimodality structured illumination microscopy (SIM), we first provide an extensive dataset of LR-SR image pairs and evaluate the deep-learning SR models in terms of structural complexity, signal-to-noise ratio and upscaling factor. Second, we devise the deep Fourier channel attention network (DFCAN), which leverages the frequency content difference across distinct features to learn precise hierarchical representations of high-frequency information about diverse biological structures. Third, we show that DFCAN's Fourier domain focalization enables robust reconstruction of SIM images under low signal-to-noise ratio conditions. We demonstrate that DFCAN achieves comparable image quality to SIM over a tenfold longer duration in multicolor live-cell imaging experiments, which reveal the detailed structures of mitochondrial cristae and nucleoids and the interaction dynamics of organelles and cytoskeleton.

Fourteen-Day Tegoprazan-Amoxicillin Dual Therapy as the First-Line Treatment of Helicobacter pylori Infection (SHARE2301): A Multicenter, Noninferiority, Randomized Clinical Trial.

BACKGROUND: Potassium-competitive acid blockers have demonstrated enormous potential in the eradication treatment of Helicobacter pylori infection, with tegoprazan being one of the representatives. The available data on the safety and efficacy of tegoprazan in dual therapy are limited. MATERIALS AND METHODS: The multicenter, noninferiority, randomized-controlled trial was conducted from May 2023 to March 2024. Treatment-naive subjects were randomly assigned (1:1) to enter either the tegoprazan-amoxicillin (TA) group (tegoprazan 50 mg twice daily and amoxicillin 750 mg four times daily) or the esomeprazole-amoxicillin (EA) group (esomeprazole 20 mg and amoxicillin 750 mg all four times daily), with a duration for 14 days. The primary outcome was eradication rate as determined by 13C-urea breath test, including per-protocol (PP) analysis and intention-to-treat (ITT) analysis. Secondary outcomes were adverse events and compliance. RESULTS: A total of 368 individuals were included in the randomization. The eradication rates in the EA group and the TA group were 84.2% and 85.8%, respectively, according to an ITT analysis (p = 0.77), and 88.5% and 88.2%, respectively, according to PP analysis (p = 1.00). The eradication rates for the TA group were not inferior to those of the EA group in both PP (p = 0.0023) and ITT analyses (p = 0.0009). There were no significant statistical differences in the incidence of adverse events and compliance between the two groups. The multivariate logistic regression analysis revealed that poor compliance increased the risk of eradication failure (p < 0.001). CONCLUSIONS: Dual therapy containing tegoprazan is safe and effective to be considered as a clinical first-line treatment option, but further optimization involving antimicrobial susceptibility testing and adjustments in dosage and frequency is warranted. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT05870683.

Evaluation of a modified ultrasound-assisted technique for mid-thoracic epidural placement: a prospective observational study.

BACKGROUND: Although mid-thoracic epidural analgesia benefits patients undergoing major surgery, technical difficulties often discourage its use. Improvements in technology are warranted to improve the success rate on first pass and patient comfort. The previously reported ultrasound-assisted technique using a generic needle insertion site failed to demonstrate superiority over conventional landmark techniques. A stratified needle insertion site based on sonoanatomic features may improve the technique. METHODS: Patients who presented for elective abdominal or thoracic surgery requesting thoracic epidural analgesia for postoperative pain control were included in this observational study. A modified ultrasound-assisted technique using a stratified needle insertion site based on ultrasound images was adopted. The number of needle passes, needle skin punctures, procedure time, overall success rate, and incidence of procedure complications were recorded. RESULTS: One hundred and twenty-eight subjects were included. The first-pass success and overall success rates were 75% (96/128) and 98% (126/128), respectively. In 95% (122/128) of patients, only one needle skin puncture was needed to access the epidural space. The median [IQR] time needed from needle insertion to access the epidural space was 59 [47-122] seconds. No complications were observed during the procedure. CONCLUSIONS: This modified ultrasound-assisted mid-thoracic epidural technique has the potential to improve success rates and reduce the needling time. The data shown in our study may be a feasible basis for a prospective study comparing our ultrasound-assisted epidural placements to conventional landmark-based techniques.

A Zn(II) Coordination Polymer for Fluorescent Turn-Off Selective Sensing of Heavy Metal Cation and Toxic Inorganic Anions.

A novel coordination polymer [Zn(atyha)2]n (1) (Hatyha = 2-(2-aminothiazole-4-yl)-2- hydroxyiminoacetic acid) was constructed by hydrothermal reaction of Zn2+ with Hatyha ligand. CP 1 exhibits a 2D (4,4)-connected topological framework with Schläfli symbol of {44·62}, where atyha- anions serve as tridentate ligands, bridging with Zn2+ through carboxylate, thiazole and oxime groups. CP 1 displays a strong ligand-based photoluminescence at 390 nm in the solid state, and remains significantly structurally stable in water. Interestingly, it can be utilized as a fluorescent probe for selective and sensitive sensing of Fe3+, Cr2O72- and MnO4- through the fluorescent turn-off effect with limit of detection (LOD) of 3.66 × 10-6, 2.38 × 10-5 and 2.94 × 10-6 M, respectively. Moreover, the efficient recyclability for detection of Fe3+ and Cr2O72- is better than that for MnO4-. The mechanisms of fluorescent quenching involve reversible overlap of UV-Vis absorption bands of the analytes (Fe3+, Cr2O72- and MnO4-) with fluorescence excitation and emission bands for CP 1, respectively.

Managing faba bean wilt disease through intercropping with wheat and reasonable nitrogen application: enhancing nutrient absorption and biochemical resistance in faba beans.

Faba bean wilt disease is a key factor limiting its production. Intercropping of faba bean with wheat has been adopted as a prevalent strategy to mitigate this disease. Nitrogen fertilizer improves faba bean yield, yet wilt disease imposes limitations. However, faba bean-wheat intercropping is effective in controlling wilt disease. To investigate the effect of intercropping under varying nitrogen levels on the incidence of faba bean wilt disease, nutrient uptake, and biochemical resistance in faba bean. Field and pot experiments were conducted in two cropping systems: faba bean monocropping (M) and faba bean-wheat intercropping (I). At four nitrogen levels, we assessed the incidence rate of wilt disease, quantified nutrient uptake, and evaluated biochemical resistance indices of plants. The application of N decreased the incidence rate of wilt disease, with the lowest reduction observed in intercropping at the N2 level. N application at levels N1, N2, and N3 enhanced the content of N, P, K, Fe, and Mn as well as superoxide dismutase (SOD), phenylalanine ammonia lyase (PAL), and polyphenol oxidase (PPO) activities and defense gene expression in monocultured plants. Additionally, these levels increased the contents of total phenols, flavonoids, soluble sugars, and soluble proteins, and all reached their maximum in intercropping at the N2 level. The application of intercropping and N effectively controlled the occurrence of faba bean wilt disease by promoting nutrient absorption, alleviating peroxidation stress, and enhancing resistance in plants. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01466-1.

Cucumis sativus PHLOEM PROTEIN 2-A1 like gene positively regulates salt stress tolerance in cucumber seedlings.

PHLOEM PROTEIN 2-A1 like (PP2-A1) gene is a member of the PP2 multigene family, and the protein encoded by which has the function of stress defense. Based on our previous proteomic study of cucumber phloem sap, CsPP2-A1 protein expression was significantly enriched under salt stress. In this paper, we obtained CsPP2-A1 interfering (CsPP2-A1-RNAi) cucumber by Agrobacterium tumefaciens-mediated method. The phenotypic changes of wild-type (WT) cucumber, CsPP2-A1-overexpressing (OE) cucumber, and CsPP2-A1-RNAi cucumber under salt treatment were observed and compared. Furthermore, physiological indicators were measured in four aspects: osmoregulation, membrane permeability, antioxidant system, and photosynthetic system. The analysis of contribution and correlation for each variable were conducted by principal component analysis (PCA) and Pearson's correlation coefficient. The above results showed that CsPP2-A1-RNAi cucumber plants exhibited weaker salt tolerance compared to WT cucumber and CsPP2-A1-OE cucumber plants in terms of phenotype and physiological indicators in response to salt stress, while CsPP2-A1-OE cucumber always showed the robust salt tolerance. Together, these results indicated that CsPP2-A1 brought a salinity tolerance ability to cucumber through osmoregulation and reactive oxygen species (ROS) homeostasis. The results of the study provided evidence for the function of CsPP2-A1 in plant salt tolerance enhancement, and they will serve as a reference for future salt-tolerant cucumber genetic manipulation.

Few-shot learning for medical text: A review of advances, trends, and opportunities.

BACKGROUND: Few-shot learning (FSL) is a class of machine learning methods that require small numbers of labeled instances for training. With many medical topics having limited annotated text-based data in practical settings, FSL-based natural language processing (NLP) holds substantial promise. We aimed to conduct a review to explore the current state of FSL methods for medical NLP. METHODS: We searched for articles published between January 2016 and October 2022 using PubMed/Medline, Embase, ACL Anthology, and IEEE Xplore Digital Library. We also searched the preprint servers (e.g., arXiv, medRxiv, and bioRxiv) via Google Scholar to identify the latest relevant methods. We included all articles that involved FSL and any form of medical text. We abstracted articles based on the data source, target task, training set size, primary method(s)/approach(es), and evaluation metric(s). RESULTS: Fifty-one articles met our inclusion criteria-all published after 2018, and most since 2020 (42/51; 82%). Concept extraction/named entity recognition was the most frequently addressed task (21/51; 41%), followed by text classification (16/51; 31%). Thirty-two (61%) articles reconstructed existing datasets to fit few-shot scenarios, and MIMIC-III was the most frequently used dataset (10/51; 20%). 77% of the articles attempted to incorporate prior knowledge to augment the small datasets available for training. Common methods included FSL with attention mechanisms (20/51; 39%), prototypical networks (11/51; 22%), meta-learning (7/51; 14%), and prompt-based learning methods, the latter being particularly popular since 2021. Benchmarking experiments demonstrated relative underperformance of FSL methods on biomedical NLP tasks. CONCLUSION: Despite the potential for FSL in biomedical NLP, progress has been limited. This may be attributed to the rarity of specialized data, lack of standardized evaluation criteria, and the underperformance of FSL methods on biomedical topics. The creation of publicly-available specialized datasets for biomedical FSL may aid method development by facilitating comparative analyses.

Ultrasound-assisted lumbar puncture with a horizontal and perpendicular paramedian approach based on positioning in patients with abnormal spinal anatomy: a case report and technical description.

BACKGROUND: The use of ultrasound has been reported to be beneficial in challenging neuraxial procedures. The angled probe is responsible for the main limitations of previous ultrasound-assisted techniques. We developed a novel technique for challenging lumbar puncture, aiming to locate the needle entry point which allowed for a horizontal and perpendicular needle trajectory and thereby addressed the drawbacks of earlier ultrasound-assisted techniques. CASE PRESENTATION: Patient 1 was an adult patient with severe scoliosis who underwent a series of intrathecal injections of nusinersen. The preprocedural ultrasound scan revealed a cephalad probe's angulation (relative to the edge of the bed) in the paramedian sagittal oblique view, and then the probe was rotated 90° into a transverse plane and we noted that a rocking maneuver was required to obtain normalized views. Then the shoulders were moved forward to eliminate the need for cephalad angulation of the probe. The degree of rocking was translated to a lateral offset from the midline of the spine through an imaginary lumbar puncture's triangle model, and a needle entry point was marked. The spinal needle was advanced through this marking-point without craniocaudal and lateromedial angulation, and first-pass success was achieved in all eight lumbar punctures. Patient 2 was an elderly patient with ankylosing spondylitis who underwent spinal anesthesia for transurethral resection of the prostate. The patient was positioned anteriorly obliquely to create a vertebral rotation that eliminated medial angulation in the paramedian approach. The procedure succeeded on the first pass. CONCLUSIONS: This ultrasound-assisted paramedian approach with a horizontal and perpendicular needle trajectory may be a promising technique that can help circumvent challenging anatomy. Larger case series and prospective studies are warranted to define its superiority to alternative approaches of lumbar puncture for patients with difficulties.

Treatment of coking wastewater using a needle coke electro-Fenton cathode: optimizing of COD, NH4+-N, and TOC removal and characterization of pollutants.

Coking wastewater is a typical organic refractory wastewater characterized by high chemical oxygen demand (COD), NH4+-N, and total organic carbon (TOC). Herein, coking wastewater was treated using a heterogeneous electro-Fenton (EF) system comprising a novel iron-loaded needle coke composite cathode (Fe-NCCC) and a dimensionally stable anode. The response surface methodology was used to optimize the reaction conditions. The predicted and actual COD removal rates were 92.13 and 89.96% under optimum conditions of an applied voltage of 4.92 V, an electrode spacing of 2.29 cm, and an initial pH of 3.01. The optimized removal rate of NH4+-N and TOC was 84.12 and 73.44%, respectively. The color of coking wastewater decreased from 250-fold to colorless, and the BOD5/COD increased from 0.126 to 0.34. Gas chromatography-mass spectrometry and Fourier transform infrared spectroscopy show that macromolecular heterocyclic organic compounds decomposed into straight-chain small molecules and even completely mineralized. The energy consumption of the EF process was 23.5 RMB Yuan per cubic meter of coking wastewater. The EF system comprising the Fe-NCCC can effectively remove pollutants from coking wastewater, has low electricity consumption, and can simultaneously reduce various pollution indicators with potential applications in the treatment of high-concentration and difficult-to-degrade organic wastewater.

Occurrence, sources and risk of heavy metals in soil from a typical antimony mining area in Guizhou Province, China.

Antimony mining activities can result in serious contamination of soil by heavy metals, which represents a risk to human health. In this study, the contamination and sources of 14 heavy metals, and their risks to both ecosystem and public health from these metals at an antimony mining site in Guizhou Province in China were explored. The results showed that the mean concentrations of Hg, Cu, As, Se, Cd, Sn, Sb and Pb were 3.73, 2.49, 13.99, 38.32, 1.11, 1.61, 305.33, 1.59 times than their local background levels. Sb, Se, As and Hg presented the relatively heavy pollution, wherein Sb (EI = 2137.34 > 320), Hg (EI = 150.26 > 80) and As (EI = 139.92 > 80) also posed the strong ecological risk. The sources identification illustrated Hg, Pb, As, Bi, Cr, Sb, Cd and Zn were attributed to industrial activities, Ni, Co, Au and Cu (p < 0.01) were derived from a combination of a lithogeny origin and anthropogenic source, whereas Se was of natural origin. Health risk assessment demonstrated that Ni, Cr and As presented both the unacceptable noncarcinogenic and carcinogenic risk, and Sb (HI = 1.44E+03) and Cd (HI = 2.91E+00) posed unacceptable noncarcinogenic risk to the local resident. Furthermore, children in the 1-6 age group (HI = 7.83E+02) were more sensitive to noncarcinogenic risk, and the 6-18 age group (CRI = 2.39E-02) as more prone to carcinogenic risk. The dermal contact was the predominant exposure pathway of noncarcinogenic and carcinogenic risks with a contribution rate of over 97% for all age groups. Overall, this research provided the comprehensive information on heavy metals in an antimony mining sites, and the related heavy metals should be paid attention for ensuring soil safety and protecting local people's health.

Intercropping alleviated the phytotoxic effects of cinnamic acid on the root cell wall structural resistance of faba bean and reduced the occurrence of Fusarium wilt.

Soilborne Fusarium wilt is a key factor restricting the cultivation of faba bean. Intercropping faba bean and wheat effectively alleviate faba bean Fusarium wilt. This study analyzed the mechanism by which cinnamic acid promotes Fusarium wilt and the mechanism that enables intercropping alleviated Fusarium wilt. Faba beans were inoculated with Fusarium oxysporum f. sp. fabae (FOF), while the controls were not inoculated. Different concentrations of cinnamic acid were added to the inoculated plants to study the occurrence of Fusarium wilt, seedling growth, the activities of cell wall degradation enzyme (CWDESs) produced by FOF in the root, defense enzymes, total phenolics and lignin, levels of expression of the pathogenesis-related genes (PRs) PR1, PR2, and PR10, and changes in the submicroscopic cell wall structure of the roots under monocropping and intercropping systems. Cinnamic acid increased the activities of CWDEs produced by FOF in the roots, increased the activities of phenylalanine ammonia lyase and polyphenol oxidase and the contents of total phenolics and lignin, and upregulated the levels of expression of PRs in the root, but it decreased the activity of peroxidase. Transmission electron microscopy (TEM) observations identified severe damage and disruption of the root cell walls, and numerous FOF mycelia entered the cytoplasm from the cell wall. The combination of these factors increased the occurrence of Fusarium wilt. The activities of CWDEs produced by FOF in the roots decreased by intercropping wheat with faba bean, which increased the resistance of the root cell walls to infection and decreased the Fusarium wilt.

High-efficiency mechanically assisted alkaline extraction of nanoparticles from biological tissues for spICP-MS analysis.

The widespread use and increased exposure of nanoparticles call for technology to quantify their concentration and size distribution in biological matrices. As ex situ evaluation, facile extraction with high fidelity and efficiency is critical. In this work, single particle inductively coupled plasma mass spectrometry (spICP-MS) was used for nanoparticle number and distribution analysis, where a facile and highly efficient mechanically assisted alkaline digestion has been developed to extract nanoparticles at low alkali concentration. The optimization was performed using chicken tissues in vitro mixed with 30 nm gold nanoparticles, mixture of 30 nm and 60 nm gold nanoparticles, and 45 nm silver nanoparticles, respectively, which is, then, mechanically ground to form tissue homogenate and 2% TMAH is added. The nanoparticles are extracted with a recovery of more than 94% for all the spiked nanoparticle tissue samples. The extraction method has also been attempted to be applied to extract single-sized gold nanoparticles from various organs of mice mixed in vivo with the nanoparticles through intravenous injection, and led to consistent results with acid digestion. Mice injected intravenously with double-sized gold nanoparticle mixture were also studied, further showing that gold nanoparticles of 30 nm and 60 nm have no significant difference in their biodistribution in the same organ. To the best of our knowledge, this is the first attempt for multiple nanoparticles being extracted simultaneously and measured quantitatively from various organs, such as the heart, liver, spleen, lungs, and kidneys. We believe this method is beneficial to the safety assessment and toxicokinetics studies for nanoparticles in tissues.

EN1 Regulates Cell Growth and Proliferation in Human Glioma Cells via Hedgehog Signaling.

Glioblastoma is an aggressive cancer of the nervous system that accounts for the majority of brain cancer-related deaths. Through cross-species transcriptome studies, we found that Engrailed 1 (EN1) is highly expressed in serum-free cultured glioma cells as well as glioma tissues, and increased expression level predicts a worse prognosis. EN1 controls glioma cell proliferation, colony formation, migration, and tumorigenic capacity in vivo. It also influences sensitivity of glioma cells to γ-ray irradiation by regulating intracellular ROS levels. Mechanistically, EN1 influences Hedgehog signaling by regulating the level of Gli1 as well as primary cilia length and the primary cilia transport-related protein TULP3. In conclusion, we demonstrate that EN1 acts as an oncogenic regulator that contributes to glioblastoma pathogenesis and could serve as a diagnostic/prognostic marker and therapeutic target for glioblastoma.

Mechanism and Regulation of Microglia Polarization in Intracerebral Hemorrhage.

Intracerebral hemorrhage (ICH) is the most lethal subtype of stroke, but effective treatments are lacking, and neuroinflammation plays a key role in the pathogenesis. In the innate immune response to cerebral hemorrhage, microglia first appear around the injured tissue and are involved in the inflammatory cascade response. Microglia respond to acute brain injury by being activated and polarized to either a typical M1-like (pro-inflammatory) or an alternative M2-like (anti-inflammatory) phenotype. These two polarization states produce pro-inflammatory or anti-inflammatory. With the discovery of the molecular mechanisms and key signaling molecules related to the polarization of microglia in the brain, some targets that regulate the polarization of microglia to reduce the inflammatory response are considered a treatment for secondary brain tissue after ICH damage effective strategies. Therefore, how to promote the polarization of microglia to the M2 phenotype after ICH has become the focus of attention in recent years. This article reviews the mechanism of action of microglia's M1 and M2 phenotypes in secondary brain injury after ICH. Moreover, it discusses compounds and natural pharmaceutical ingredients that can polarize the M1 to the M2 phenotype.

SARS-CoV-2 and SARS-CoV: Virtual screening of potential inhibitors targeting RNA-dependent RNA polymerase activity (NSP12).

Since the outbreak of severe acute respiratory syndrome (SARS) in 2003, the harm caused by coronaviruses to the world cannot be underestimated. Recently, a novel coronavirus (severe acute respiratory syndrome coronavirus-2 [SARS-CoV-2]) initially found to trigger human severe respiratory illness in Wuhan City of China in 2019, has infected more than six million people worldwide by 21 June 2020, and which has been recognized as a public health emergency of international concern as well. And the virus has spread to more than 200 countries around the world. However, the effective drug has not yet been officially licensed or approved to treat SARS-Cov-2 and SARS-Cov infection. NSP12-NSP7-NSP8 complex of SARS-CoV-2 or SARS-CoV, essential for viral replication and transcription, is generally regarded as a potential target to fight against the virus. According to the NSP12-NSP7-NSP8 complex (PDB ID: 7BW4) structure of SARS-CoV-2 and the NSP12-NSP7-NSP8 complex (PDB ID: 6NUR) structure of SARS-CoV, NSP12-NSP7 interface model, and NSP12-NSP8 interface model were established for virtual screening in the present study. Eight compounds (Nilotinib, Saquinavir, Tipranavir, Lonafarnib, Tegobuvir, Olysio, Filibuvir, and Cepharanthine) were selected for binding free energy calculations based on virtual screening and docking scores. All eight compounds can combine well with NSP12-NSP7-NSP8 in the crystal structure, providing drug candidates for the treatment and prevention of coronavirus disease 2019 and SARS.