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Allenes are a class of unsaturated compounds containing a propadiene structural moiety, exhibiting essential physiological, pharmacological, and various reactivities. Their (4 ​+ ​3) cycloaddition reaction has become an effective method for synthesizing seven-membered rings, especially for heterocycles. This method has been continuously improved and developed. Herein, we review the (4 ​+ ​3) cycloaddition of allenes, focusing on the developed methodologies and the outlook in this field from 2013 to 2023.

Abstract Intracellular trafficking, an extremely complex network, dynamically orchestrates nearly all cellular activities. A versatile method that enables the manipulation of target transport pathways with high spatiotemporal accuracy in vitro and in vivo is required to study how this network coordinates its functions. Here, a new method called RIVET (Rapid Immobilization of target Vesicles on Engaged Tracks) is presented. Utilizing inducible dimerization between target vesicles and selective cytoskeletons, RIVET can spatiotemporally halt numerous intracellular trafficking pathways within seconds in a reversible manner. Its highly specific perturbations allow for the real‐time dissection of the dynamic relationships among different trafficking pathways. Moreover, RIVET is capable of inhibiting receptor‐mediated endocytosis. This versatile system can be applied from the cellular level to whole organisms. RIVET opens up new avenues for studying intracellular trafficking under various physiological and pathological conditions and offers potential strategies for treating trafficking‐related disorders.

Abstract Cardiac pacemakers play a crucial role in arrhythmia treatment. Existing devices typically rely on rigid electrode components, leading to potential issues such as heart damage and detachment during prolonged cardiac motion due to the mechanical mismatch with cardiac tissue. Additionally, traditional pacemakers, with their batteries and percutaneous leads, introduce infection risks and limit freedom of movement. A wireless, battery‐free multifunctional bioelectronic device for cardiac pacing is developed. This device integrates highly conductive (160 S m−1), flexible (Young's modulus of 80 kPa is similar to that of mammalian heart tissue), and stretchable (270%) soft hydrogel electrodes, providing high signal‐to‐noise ratio (≈28 dB) electrocardiogram (ECG) recordings and effective pacing of the beating heart. The versatile device detects physiological and biochemical signals in the cardiac environment and allows for adjustable pacing in vivo studies. Remarkably, it maintained recording and pacing capabilities 31 days post‐implantation in rats. Additionally, the wireless bioelectronic device can be fully implanted in rabbits for pacing. By addressing a major shortcoming of conventional pacemakers, this device paves the way for implantable flexible bioelectronics, which offers promising opportunities for advanced cardiac therapies.

Individuals with neurodevelopmental disorders (NDDs) are frequently diagnosed with comorbidities in other organs, indicating that NDD risk genes may have extra-cerebral functions. The engineered mouse models are pivotal in understanding the functions of candidate NDD genes. Here, we report that Emx1-Cre and nestin-Cre mouse strains, the popular tools to study brain development, also exhibit recombination activity in the kidney. We find that both Emx1-Cre and nestin-Cre can drive recombination in epithelial cells lining proximal and distal convoluted tubules of the nephron. Additionally, nestin-Cre drives recombination in the glomerulus of the nephron. Furthermore, we use Emx1-Cre and nestin-Cre to knock out Larp7, a gene linked to a human NDD called Alazami syndrome. We find that Larp7 knockout using nestin-Cre, but not Emx1-Cre, results in elevated blood urea nitrogen. This result suggests a compromised kidney function, reminiscent of recently revealed renal anomalies in Alazami syndrome patients. Many genes have been knocked out using Emx1-Cre and nestin-Cre to study their roles during embryonic neurogenesis. It will be of great interest to reinvestigate whether the renal development and function is affected in these existing mouse models.

Abstract A pressing challenge in spatially resolved transcriptomics (SRT) is to benchmark the computational methods. A widely-used approach involves utilizing simulated data. However, biases exist in terms of the currently available simulated SRT data, which seriously affects the accuracy of method evaluation and validation. Herein, we present scCube ( https://github.com/ZJUFanLab/scCube ), a Python package for independent, reproducible, and technology-diverse simulation of SRT data. scCube not only enables the preservation of spatial expression patterns of genes in reference-based simulations, but also generates simulated data with different spatial variability (covering the spatial pattern type, the resolution, the spot arrangement, the targeted gene type, and the tissue slice dimension, etc.) in reference-free simulations. We comprehensively benchmark scCube with existing single-cell or SRT simulators, and demonstrate the utility of scCube in benchmarking spot deconvolution, gene imputation, and resolution enhancement methods in detail through three applications.

Purpose Prostate cancer (PCa) is an epithelial malignancy that originates in the prostate gland and is generally categorized into low, intermediate, and high-risk groups. The primary diagnostic indicator for PCa is the measurement of serum prostate-specific antigen (PSA) values. However, reliance on PSA levels can result in false positives, leading to unnecessary biopsies and an increased risk of invasive injuries. Therefore, it is imperative to develop an efficient and accurate method for PCa risk stratification. Many recent studies on PCa risk stratification based on clinical data have employed a binary classification, distinguishing between low to intermediate and high risk. In this paper, we propose a novel machine learning (ML) approach utilizing a stacking learning strategy for predicting the tripartite risk stratification of PCa. Methods Clinical records, featuring attributes selected using the lasso method, were utilized with 5 ML classifiers. The outputs of these classifiers underwent transformation by various nonlinear transformers and were then concatenated with the lasso-selected features, resulting in a set of new features. A stacking learning strategy, integrating different ML classifiers, was developed based on these new features. Results Our proposed approach demonstrated superior performance, achieving an accuracy of 0.83 and an area under the receiver operating characteristic curve value of 0.88 in a dataset comprising 197 PCa patients with 42 clinical characteristics. Conclusions This study aimed to improve clinicians’ ability to rapidly assess PCa risk stratification while reducing the burden on patients. This was achieved by using artificial intelligence-related technologies as an auxiliary method for diagnosing PCa.

Abstract Physisorption relying on crystalline porous materials offers prospective avenues for sustainable separation processes, greenhouse gas capture, and energy storage. However, the lack of end-to-end deep learning model for adsorption prediction confines the rapid and precise screen of crystalline porous materials. Here, we present DeepSorption, a spatial atom interaction learning network that realizes accurate, fast, and direct structure-adsorption prediction with only information of atomic coordinate and chemical element types. The breakthrough in prediction is attributed to the awareness of global structure and local spatial atom interactions endowed by the developed Matformer, which provides the intuitive visualization of atomic-level thinking and executing trajectory in crystalline porous materials prediction. Complete adsorption curves prediction could be performed using DeepSorption with a higher accuracy than Grand canonical Monte Carlo simulation and other machine learning models, a 20-35% decline in the mean absolute error compared to graph neural network CGCNN and machine learning models based on descriptors. Since the established direct associations between raw structure and target functions are based on the understanding of the fundamental chemistry of interatomic interactions, the deep learning network is rationally universal in predicting the different physicochemical properties of various crystalline materials.

Pseudomonas aeruginosa is pathogenic in immunocompromised individuals. It has several complex mechanisms for evading human immunity. The objective of the study was to examine the secretory immunoglobulin A (sIgA) mediated immune response in saliva to detect P. aeruginosa in pulmonary tuberculosis.

Abstract Background Non-invasive risk stratification contributes to the precise treatment of prostate cancer (PCa). In previous studies, lymphocyte subsets were used to differentiate between low-/intermediate-risk and high-risk PCa, with limited clinical value and poor interpretability. Based on functional subsets of peripheral lymphocyte with the largest sample size to date, this study aims to construct an easy-to-use and robust nomogram to guide the tripartite risk stratifications for PCa. Methods We retrospectively collected data from 2039 PCa and benign prostate disease (BPD) patients with 42 clinical characteristics on functional subsets of peripheral lymphocyte. After quality control and feature selection, clinical data with the optimal feature subset were utilized for the 10-fold cross-validation of five Machine Learning (ML) models for the task of predicting low-, intermediate- and high-risk stratification of PCa. Then, a novel clinic-ML nomogram was constructed using probabilistic predictions of the trained ML models via the combination of a multivariable Ordinal Logistic Regression analysis and the proposed feature mapping algorithm. Results 197 PCa patients, including 56 BPD, were enrolled in the study. An optimal subset with nine clinical features was selected. Compared with the best ML model and the clinic nomogram, the clinic-ML nomogram achieved the superior performance with a sensitivity of 0.713 (95% CI 0.573–0.853), specificity of 0.869 (95% CI 0.764–0.974), F1 of 0.699 (95% CI 0.557–0.841), and AUC of 0.864 (95% CI 0.794–0.935). The calibration curve and Decision Curve Analysis (DCA) indicated the predictive capacity and net benefits of the clinic-ML nomogram were improved. Conclusion Combining the interpretability and simplicity of a nomogram with the efficacy and robustness of ML models, the proposed clinic-ML nomogram can serve as an insight tool for preoperative assessment of PCa risk stratifications, and could provide essential information for the individual diagnosis and treatment in PCa patients.

To prevent in a short time the rapid increase of tourists and corresponding traffic restriction measures’ lack in scenic areas, this study established a prediction model based on an improved convolutional neural network (CNN) and long- and short-term memory (LSTM) combined neural network. The study used this to predict the inflow and outflow of tourists in scenic areas. The model uses a residual unit, batch normalization, and principal component analysis to improve the CNN. The experimental results show that the model works best when batches’ quantity is 10, neurons’ quantity in the LSTM layer is 50, and the number of iterations is 50 on a workday; on non-working days, it is best to choose 10, 100, or 50. Using root mean square error (RMSE), normalized root mean square error (NRMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) as evaluation indicators, the inflow and outflow RMSEs of this study model are 82.51 and 89.80, MAEs are 26.92 and 30.91, NRMSEs are 3.99 and 3.94, and MAPEs are 1.55 and 1.53. Among the various models, this research model possesses the best prediction function. This provides a more accurate prediction method for the prediction of visitors’ flow rate in scenic spots. Meanwhile, the research model is also conducive to making corresponding flow-limiting measures to protect the ecology of the scenic area.

Abstract Tissues are highly complicated with spatial heterogeneity in gene expression. However, the cutting-edge single-cell RNA-seq technology eliminates the spatial information of individual cells, which contributes to the characterization of cell identities. Herein, we propose single-cell spatial position associated co-embeddings (scSpace), an integrative method to identify spatially variable cell subpopulations by reconstructing cells onto a pseudo-space with spatial transcriptome references (Visium, STARmap, Slide-seq, etc.). We benchmark scSpace with both simulated and biological datasets, and demonstrate that scSpace can accurately and robustly identify spatially variated cell subpopulations. When employed to reconstruct the spatial architectures of complex tissue such as the brain cortex, the small intestinal villus, the liver lobule, the kidney, the embryonic heart, and others, scSpace shows promising performance on revealing the pairwise cellular spatial association within single-cell data. The application of scSpace in melanoma and COVID-19 exhibits a broad prospect in the discovery of spatial therapeutic markers.

Current methods to reanalyze bulk RNA-seq at spatially resolved single-cell resolution have limitations. Here, the authors develop Bulk2Space, a spatial deconvolution algorithm using single-cell and spatial transcriptomics as references, providing new insights into spatial heterogeneity within bulk tissue.

Objective: This study aimed to investigate the factors influencing the oil yield of rapeseed during pressing in a double screw oil press. Methods: To simulate the pressing process of rapeseed and to explore the effects of two factors, the speed of the press screw and the porosity, on the oil yield. Results: The oil yield of rapeseed was linearly related to the porosity, and a larger porosity, was associated with a lower oil yield. Moreover, the oil yield was negatively related to the speed of the press screw. Conclusion: The oil yield of rapeseed was highest when the porosity was 0.45 with the speed of pressing screw at 20 r/min.

Objective: This study aimed to establish a new method for detecting furfurals in tea. Methods: A gas chromatography tandem mass spectrometry (GC-MS/MS) method was established for the simultaneous determination of furfural, 5-methylfurfural, 5-hydroxymethylfurfural and 2-Acetylfuran in tea. The sample pretreatment method and GC-MS/MS method were optimized. Furfural-D4 was used as the internal standard. The sample was extracted by acetonitrile, treated and purified by QuEChERS method, and determined by GC-MS/MS multi reaction monitoring (MRM). Results: The four furfurals showed good linear relationship in the mass concentration range of 1.25~200.00 μg/L, with the correlation coefficient ≥0.999 0, and the detection limit (S/N=3) was 1 μg/kg, with the recovery range of standard addition of 89.10%~113.02%. Most of the commercially available tea samples were found to contain furfural. Conclusion: This method in the present study is simple, rapid and can eliminate the interference of complex matrix in tea. The result is accurate, reliable and sensitive. It is suitable for the simultaneous determination of four furfurals in tea.

Wildfires are expected to increase in frequency and severity. Here the authors use geochemical paleo-reconstructions to show that over decadal timescales in Earth history wildfires are positively correlated with phytoplankton production off the coast of Australia.

Black carbon accumulation rates in hadal trenches in the deepest regions of the oceans could be seven-fold higher than the global ocean average, according to geochemical and isotopic analyses of sediments from six trenches in the Pacific Ocean.

BackgroundVentricular fibrillation (VF) is a common arrhythmia that occurs after the release of aortic cross-clamp (ACC) in patients undergoing cardiopulmonary bypass (CPB) surgery. Repeated defibrillation and long duration of VF could increase myocardial injuries. In patients with left ventricular hypertrophy (LVH), VF is easier to occur and more difficult to be terminated. Amiodarone, known as class III antiarrhythmic agent, has the prominent properties of converting VF and restoring the sinus rhythm. Before ACC release, administration of amiodarone has been confirmed useful to reduce occurrence of VF. However, few studies are focused on the effect of amiodarone before ACC release on reducing VF in patients with LVH. ObjectiveThis study aimed at determining the efficacy of prophylactic intravenous amiodarone administration on reperfusion VF after release of ACC in patients with LVH undergoing CPB surgery. MethodsThis will be a prospective, randomized, double-blind, placebo-controlled trial. The trial will enroll 54 patients with LVH aged 18-75 years who will undergo CPB surgery. All eligible participants will be randomly allocated to either the amiodarone or placebo group by using the block randomization in a 1:1 ratio. The primary end point will be the incidence rate of VF 30 minutes after ACC release and be assessed using the Fisher exact test. All data will be analyzed in accordance with the intention-to-treat principle. ResultsThe study began in August 2022, and the data collection will take place for the next 2 academic years. As of this writing, 21 participants have already been recruited for the study. ConclusionsWith this trial, we are hoping to demonstrate that prophylactic infusion of amiodarone before ACC release could reduce the occurrence of reperfusion VF in patients with LVH. Trial RegistrationClinicalTrials.gov ChiCTR2000035057; https://www.chictr.org.cn/showprojen.aspx?proj=57145 International Registered Report Identifier (IRRID)DERR1-10.2196/40115

Hydropower is one of the significant renewable energy resources. It is regularly requested at peak time steps to meet the load requirements of power systems resources allocation. Therefore, modeling the optimal operation of hydropower systems to maximize the entire energy production of reservoir systems can be a vital task for energy investment. Deriving optimal unknown decision parameters of these reservoir systems is a nonlinear, nonconvex, and complex optimization problem. Herein, a novel optimization algorithm, called an accelerated version of gradient-based optimization (AGBO), is developed to solve a complex multi-reservoir hydropower system. This advised technique uses an efficient adaptive control parameters mechanism to stabilize the global and local search; utilizing an enhanced local escaping operator (ELEO) to extend the chances of getting away from local optima; expanding the exploitation search by applying the sequential quadratic programming (SQP) technique. At first, the developed AGBO algorithm is employed to solve the optimal operation of a complex 10-reservoir hydropower system. Secondly, the possibility of the AGBO algorithm within the global optimization problems is illustrated by numerical tests of 23 mathematical benchmark functions. Optimal results show that the proposed AGBO can approach to 0.9999% of the optimal global solution. As a result, the advised method is the most superior one compared to the other advanced optimization algorithms for maximizing the load demands in hydropower system. In conclusion, this offers a productive tool to solve the complex hydropower multi-reservoir optimization systems.

Introduction: Video-assisted thoracoscopic surgical (VATS) ablation is widely performed in surgical areas to treat atrial fibrillation (AF), which is minimally invasive and highly effective. Amiodarone, known as a class III antiarrhythmic agent, has the greatest potential to maintain sinus rhythm of AF. At present, few studies focused on the efficacy of perioperative intravenous amiodarone in the VATS ablation of AF. Therefore, the trial is designed to investigate the effect of perioperative amiodarone infusion on cardioversion of AF early after VATS ablation. Methods: and analysis: This will be a prospective, randomized, double-blind, controlled trial. The trial is to enroll 182 patients aged 18–70 years who will undergo VATS ablation of AF. All eligible participants will be randomly allocated to either the amiodarone or placebo group by using the block randomization in a 1:1 ratio. The primary endpoint will be freedom from atrial arrhythmias 24 h after the VATS procedure and be assessed using the Kaplan-Meier method. All data will be analyzed in accordance with the intention-to-treat principle. Discussion: The clinical trial has been designed to investigate the efficacy of perioperative intravenous amiodarone on cardioversion of AF early after VATS ablation. We are hoping to demonstrate that perioperative infusion of amiodarone could improve the maintenance of sinus rhythm 24 h after VATS ablation.

Biochemical monitoring of bodily fluidics such as sweat, urine, and tears have been extensively developed, but reliable biochemical analysis of sputum biospecimens remains limited and challenging due to the low abundance of biomarkers in intrinsically viscous sputum. We reported a portable multi-channel sputum-based interdigitated organic electrochemical transistors (SiOECTs) device for noninvasive sputum diagnosis. We tailored the AgNWs-doped organic electrochemical transistors, integrating with multiplexed aptamer-antigen assays, to realize the signal amplification and simultaneous detection of biomarkers in raw sputum biospecimens from lung cancer patients. Clinical validation studies demonstrated favorable correlation coefficients between the sputum and serum biospecimens. By utilizing our portable multi-channel iOECTs devices, lung cancer patients were differentiated from health control with an optimum area under the curve (AUC) of 0.931, sensitivity of 87.0%, and specificity of 86.5%. Our miniaturized and portable device could even realize the continuous in-home tracking of the biomarkers change for lung cancer patients after radiotherapy/chemotherapy. It is envisaged that the SiOECTs will shed light on noninvasive diagnostics platforms for sputum-related diseases.

Summary: Testicular germ cell tumors and closely related embryonal stem cells are exquisitely sensitive to cisplatin, a feature thought to be linked to their pluripotent state and p53 status. It remains unclear whether and how cellular state is coordinated with p53 to confer cisplatin sensitivity. Here, we report that positive transcription elongation factor b (P-TEFb) determines cell fate upon DNA damage. We find that cisplatin rapidly activates P-TEFb by releasing it from inhibitory 7SK small nuclear ribonucleoprotein complex. P-TEFb directly phosphorylates pluripotency factor estrogen-related receptor beta (ESRRB), and induces its proteasomal degradation to enhance pro-survival glycolysis. On the other hand, P-TEFb is required for the transcription of a substantial portion of p53 target genes, triggering cell death during prolonged cisplatin treatment. These results reveal previously underappreciated roles of P-TEFb to coordinate the DNA damage response. We discuss the implications for using P-TEFb inhibitors to treat cancer and ameliorate cisplatin-induced ototoxicity.

Abstract The stem cell is the foundation of regenerative medicine and tissue engineering. Regulating specific stem cell fate, such as cell attachment, proliferation, differentiation, and even death, undergoes continuous development. Cold atmospheric plasma (CAP), the core technology of plasma medicine, is attracting tremendous attention due to its ability and versatility to manipulate various types of cells, including stem cells. Specifically, the direct and indirect applications of CAP in controlling cell fate are best exemplified by upfront irradiation of the stem cells and modification of the stem cell niche, respectively. This review will describe the recent advances in various CAP strategies, both direct and indirect, and their influence on the fate of healthy and cancer stem cells. Particular emphasis will be placed on the mechanism of connecting the physical and chemical cues carried by the plasma and biological changes presented by the cells, especially at the transcriptomic level. The ultimate goal is to exploit CAP’s potential in regenerative medicine.

The calculation methods of the maximum principal engineering strain,maximum principal logarithmic strain,maximum principal Green-Lagrange strain,and maximum principal Euler strain and octahedron shear strain peak under uniaxial and multiaxial loading stress condition are studied. It is found that the five damage parameters can be calculated only by outputting the deformation gradient tensor of the dangerous area in the finite element analysis. Based on the fatigue crack initiation theory and the fatigue test data of dumbbell rubber test piece,the life prediction models are established by the above five damage parameters,and the accuracy of the five life prediction models is measured by the goodness of fit value. Among them,the life prediction model with octahedron shear strain peak as damage parameter has the best fitting value. The fatigue life prediction model is established based on the fatigue crack growth theory and the crack growth test data of one-sided notch,pure shear specimen. The life prediction model with octahedral shear strain peak as damage parameter and the life prediction model based on crack growth theory were used to predict the life of the same bushing product respectively. It is found that the life prediction model with octahedral shear strain peak as damage parameter has better prediction effect,and the predicted life is near the triple scatter line of the measured life.

Chinese courts organize debates surrounding controversial issues along with the gradual formation of the new procedural system. With the progress of China's judicial reform, more than 80 million judgement documents have been made public online. Similar controversial issues identified in and among the massive public judgment documents are of significant value for judges in their trial work. Hence, homogeneous controversial issues classification becomes the basis for similar cases retrieval. However, controversial issues follow the power-law distribution, not all of them are within the labels provided by manual annotation and their categories cannot be exhausted. In order to generalize those unfamiliar categories without necessitating extensive retraining, we propose a controversial issues classification algorithm based on few-shot learning. Two few-shot learning algorithms are proposed for our controversial issues problem, Relation Network and Induction Network, respectively. With only a handful of given instances, both of them have shown excellent results on the two datasets, which proves their effectiveness in adapting to accommodating new categories not seen in training. The proposed method provides trial assistance for judges, promotes the dissemination of experience and improves fairness of adjudication.

Summary: Taxane-based reagents, such as Taxol, Taxotere, and Abraxane, are popular anti-cancer drugs that can differ in their clinical efficacy. This difference is generally attributed to their active pharmaceutical ingredients. Here, we report a serendipitous discovery that Taxol induces metabolic dysregulation and unfolded protein response. Surprisingly, these effects of Taxol are entirely dependent on its excipient, Cremophor EL (CrEL). We show that CrEL promotes aerobic glycolysis and in turn results in drastic upregulation of angiopoietin like 4 (ANGPTL4), a major regulator of human blood lipid profile. Notably, premedication with dexamethasone further enhances the expression of ANGPTL4. Consistently, we find that the amplitude and frequency of increase in triglycerides is more prominent in Taxol-treated patients with breast cancer. In addition, we find that CrEL activates the unfolded protein response pathway to trigger proinflammatory gene expression and caspase/gasdermin E-dependent pyroptosis. Finally, we discuss the implications of these results in anti-cancer therapies.

Coastal seas, including coastal bays, are the geographically critical transitional zone that links terrestrial and open oceanic ecosystems. Organic carbon cycling in this area is a dynamic and disproportionally key component in the global carbon cycle and budget. As the thermally-transformed organic carbon produced exclusively from the incomplete combustion of biomass and fossil fuels, the recalcitrance and resultant longer environmental residence times result in important implications of black carbon (BC) in the global carbon budget. However, the environmental dynamics of BC in coastal seas have not well been constrained. In this study, we conducted one seawater sampling campaign in the high-intensity BC emission influenced Bohai Bay (BHB) and Laizhou Bay (LZB) in 2013, and quantified both particulate and dissolved BC (PBC and DBC). We elaborated the distributions, sources, and associated influencing factors of PBC and DBC in BHB and LZB in 2013, and simultaneously contrasted the PBC and DBC quantity and quality under two distinct fluvial hydrological regimes of 2013 and 2014 [discussed in Fang et al. (Environ. Sci. Technol., 2021, 55, 788–796)]. Except for the overwhelmingly high PBC in northern BHB caused by anthropogenic point-source emission, horizontally, both PBC and DBC showed a seaward decreasing trend, suggesting that riverine discharge was the major source for PBC and DBC. Vertically, in contrast to the uniform concentrations of DBC between surface and bottom waters, the PBC levels in bottom waters was significantly higher than that in surface waters, which was primarily resulted from the intense sediment re-suspension process during this sampling period. The nearly simultaneous investigations in 2013 and 2014 revealed consistent spatial patterns of PBC and DBC quantity and quality. But significantly lower PBC and DBC quantity and quality were found in 2014 than in 2013, which were largely due to the significantly different climatic conditions (including the watershed hydrology and sunlit radiation) between these 2 years.

The mechanisms controlling irreversible cell cycle exit in cerebellar granule progenitors (GCPs) have not been fully elucidated. Here, the authors performed RNA-sequencing of GCPs exiting the cell cycle to identify downregulation of Brd4 activity as an early event during cell cycle exit which subsequently regulates Shh activity and is needed for proper cerebellar development

Air embolism is a rare complication of upper endoscopy and potentially causes life-threatening events. A 67-year-old man with a history of surgery of cardiac carcinoma and pancreatic neuroendocrine tumor underwent painless upper endoscopy because of tarry stools. During the procedure, air embolism developed, which caused decreased pulse oxygen saturation and delayed sedation recovery. He recovered with some weakness of the left upper limb in the intensive care unit without hyperbaric oxygen therapy. The etiology, clinical manifestations, and treatments of air embolism are discussed based on the literature reports. Although air embolism is uncommon in endoscopic examinations, the patients’ outcomes could be improved if clinicians are alert to this potential complication, and promptly start proper diagnostic and therapeutic measures.

A novel optical frequency-hopping scheme based on a flexible structure for secure optical communications is proposed and demonstrated. In the proposed scheme, critical users' data are divided into a lot of segments, and these segments are transmitted by different optical wavelengths in time domain. In other words, one channel optical carrier carries different users' data segments. A flexible structure was demonstrated and used in optical frequency-hopping system to simplify the structure and decrease the cost of the security system. In this paper, the viability of a four-wavelength-frequency-hopping secure optical communication system with a 25-Gb/s error-free transmission through a 32-km single-mode fiber and a 8-km dispersion compensation fiber was demonstrated and verified by simulation tools.

Non-invasive positive pressure ventilation (NIPPV) is a life-saving approach which was developed to reduce the complications of endotracheal intubation and invasive ventilation in patients with chronic obstructive pulmonary disease (COPD). However, it has a certain probability of invalid. Failure of NIPPV will lead to an increase in mortality, which highlights the importance of rational diagnosis about the need for NIPPV therapy. In order to avoid delaying endotracheal intubation, we proposed a hybrid model which combine tree-based feature transformation with Bayesian non-parametric classification, to predict whether the patient should adopt NIPPV based on the their own physical condition. We delved into the feature importance and justified the rationality of using tree-based feature transformation. The proposed gaussian process classification (GPC) with gradient boosting decision tree (GBDT) feature transformation model has shown state-of-the-art results on both the NIPPV dataset and two simulated datasets with larger sample size. For critically ill COPD patients, the proposed method provides diagnostic assistance for physicians' decision making and avoids delaying endotracheal intubation or mechanical ventilation.

The purpose of this study was to compare the efficacy of nucleoside analogues (NAs) in the treatment of HBV-related liver failure. The data of patients with HBV-related liver failure treated with nucleoside analogues were used to conduct a network meta-analysis. A total of 1660 patients from 12 articles about the efficacy of lamivudine, entecavir, telbivudine and tenofovir for HBV-related liver failure treatment were recruited in the study. The highest two- and three-month survival rate was recorded for patients using tenofovir. The end-stage liver disease (MELD) score and mortality in patients undergoing tenofovir treatment were the lowest. Patients treated with telbivudine had the highest one-month survival rate. Patients receiving enticavir therapy showed the lowest HBV DNA level. Our results indicate that tenofovir may be the best therapy for the treatment of HBV-related liver failure compared to other nucleoside analogues (including lamivudine, entecavir and telbivudine) and non-NAs treatment.

Abstract Background The anti-tumor activities of Natural compounds and their derivatives are of great interest to pharmaceutical industries. Fisetin is one of prospective natural compounds in this regard but unfortunately with poor hydrophilicity. Methods The effects of unmodified and modified fisetin in cultured ovarian cancer cells were compared by transmission electronmicroscopy to determine apoptotic bodies, MTT assay to quantitate cell numbers, and fluorescence activated cell sorting analyse of various markers to determine the apoptotic state. In addition, the efficacy of fisetin and fisetin-micelles in vivo was determined by using immunocompromised mice. Apoptosis was measured by established markers using both western blot analysis and immunochemistry. Angiogenesis in a xenograft mouse model carring SKOV3 cells was evaluated by color Doppler ultrasound and immunohistochemistry. Result Multiple lines of evidence indicated that fisetin and fisetin micelles induce apoptosis in ovarian cancer cells in a dose-dependent manner. Histological analysis, terminal deoxynucleotidyltransferase-mediated nick-end labeling assay, western blot, immunohistochemical detection and microvessel density detection demonstrated that fisetin and fisetin micelles induced increased tumor apoptosis, proliferation suppression and antiangiogenesis activities. Conclusion As far as we know, the present study is the first time to demonstrate the potency of both fisetin and fisetin micelles inducing apoptosis in ovarian cancer cells. Further studies will be needed to validate the therapeutic potential of fisetin and fisetin micelles in ovarian cancer treatment.

Summary: CNS cortical histogenesis depends on polarity signaling pathways that regulate cell adhesion and motility. Here we report that conditional deletion of the Rho GTPase Cdc42 in cerebellar granule cell precursors (GCPs) results in abnormalities in cerebellar foliation revealed by iDISCO clearing methodology, a loss of columnar organization of proliferating GCPs in the external germinal layer (EGL), disordered parallel fiber organization in the molecular layer (ML), and a failure to extend a leading process and form a neuron-glial junction during migration along Bergmann glia (BG). Notably, GCPs lacking Cdc42 had a multi-polar morphology and slowed migration rate. In addition, secondary defects occurred in BG development and organization, especially in the lateral cerebellar hemispheres. By phosphoproteomic analysis, affected Cdc42 targets included regulators of the cytoskeleton, cell adhesion and polarity. Thus, Cdc42 signaling pathways are critical regulators of GCP polarity and the formation of neuron-glial junctions during cerebellar development. : Optical Imaging; Developmental Neuroscience; Techniques in Neuroscience Subject Areas: Optical Imaging, Developmental Neuroscience, Techniques in Neuroscience

Parallel patterning of atoms over a large surface would represent a major advance over current serial methods of single atom manipulation. Here, the authors explore a periodic instability from liquid alloy droplets for high-throughput atom printing.

Magnetorheological fluid (MRF) damper is one of the most promising semiactive devices for vibration control. In this paper, a shear-valve mode MRF damper for pipeline vibration control is proposed. The dynamic model and the state equation of the pipeline are established and the linear quadratic regulator (LQR) is used to generate the optimal damping force of MRF damper. The design concept considering the structure and the electromagnetic properties simultaneously is discussed in detail. A mathematical model of the relation between shear stress and control current based on interpolation method is established. Finite element analysis (FEA) software COMSOL is selected to simulate the magnetic field and electromagnetism-thermal field of the MRF damper. A computational method based on the simulation model is established to calculate the shear stress. In order to reduce the magnetic leakage, a method of adding magnetism-insulators at both ends of the piston head is presented. The influence of control current, displacement, and velocity on mechanical performance of the proposed MRF damper is experimentally investigated. The test results show that the performance of the MRF damper is basically identical with the theoretical prospective and the simulation conclusions, which proves the correctness and feasibility of this design concept.

Although casein kinase 1δ (CK1δ) is at the center of multiple signaling pathways, its role in the expansion of CNS progenitor cells is unknown. Using mouse cerebellar granule cell progenitors (GCPs) as a model for brain neurogenesis, we demonstrate that the loss of CK1δ or treatment of GCPs with a highly selective small molecule inhibits GCP expansion. In contrast, CK1δ overexpression increases GCP proliferation. Thus, CK1δ appears to regulate GCP neurogenesis. CK1δ is targeted for proteolysis via the anaphase-promoting complex/cyclosome (APC/CCdh1) ubiquitin ligase, and conditional deletion of the APC/CCdh1 activator Cdh1 in cerebellar GCPs results in higher levels of CK1δ. APC/CCdh1 also downregulates CK1δ during cell-cycle exit. Therefore, we conclude that APC/CCdh1 controls CK1δ levels to balance proliferation and cell-cycle exit in the developing CNS. Similar studies in medulloblastoma cells showed that CK1δ holds promise as a therapeutic target.

MicroRNAs (miRNAs) have gradually been recognized as regulators of embryonic development; however, relatively few miRNAs have been identified that regulate cardiac development. A series of recent papers have established an essential role for the miRNA-17-92 (miR-17-92) cluster of miRNAs in the development of the heart. Previous research has shown that the Friend of Gata-2 (FOG-2) is critical for cardiac development. To investigate the possibility that the miR-17-92 cluster regulates FOG-2 expression and inhibits proliferation in mouse embryonic cardiomyocytes we initially used bioinformatics to analyze 3’ untranslated regions (3’UTR) of FOG-2 to predict the potential of miR-17-92 to target it. We used luciferase assays to demonstrate that miR-17-5p and miR-20a of miR-17-92 interact with the predicted target sites in the 3’UTR of FOG-2. Furthermore, RT-PCR and Western blot were used to demonstrate the post-transcriptional regulation of FOG-2 by miR-17-92 in embryonic cardiomyocytes from E12.5-day pregnant C57BL/6J mice. Finally, EdU cell assays together with the FOG-2 rescue strategy were employed to evaluate the effect of proliferation on embryonic cardiomyocytes. We first found that the miR-17-5p and miR-20a of miR-17-92 directly target the 3’UTR of FOG-2 and post-transcriptionally repress the expression of FOG-2. Moreover, our findings demonstrated that over-expression of miR-17-92 may inhibit cell proliferation via post-transcriptional repression of FOG-2 in embryonic cardiomyocytes. These results indicate that the miR-17-92 cluster regulates the expression of FOG-2 protein and suggest that the miR-17-92 cluster might play an important role in heart development.