HBO1 determines SMAD action in pluripotency and mesendoderm specification.

TGF-ß signaling family plays an essential role to regulate fate decisions in pluripotency and lineage specification. How the action of TGF-ß family signaling is intrinsically executed remains not fully elucidated. Here, we show that HBO1, a MYST histone acetyltransferase (HAT) is an essential cell intrinsic determinant for TGF-ß signaling in human embryonic stem cells (hESCs). HBO1-/- hESCs fail to response to TGF-ß signaling to maintain pluripotency and spontaneously differentiate into neuroectoderm. Moreover, HBO1 deficient hESCs show complete defect in mesendoderm specification in BMP4-triggered gastruloids or teratomas. Molecularly, HBO1 interacts with SMAD4 and co-binds the open chromatin labeled by H3K14ac and H3K4me3 in undifferentiated hESCs. Upon differentiation, HBO1/SMAD4 co-bind and maintain the mesoderm genes in BMP4-triggered mesoderm cells while lose chromatin occupancy in neural cells induced by dual-SMAD inhibition. Our data reveal an essential role of HBO1, a chromatin factor to determine the action of SMAD in both human pluripotency and mesendoderm specification.

Large-scale expansion of human umbilical cord-derived mesenchymal stem cells using PLGA@PLL scaffold.

Mesenchymal stem cells (MSCs) are highly important in biomedicine and hold great potential in clinical treatment for various diseases. In recent years, the capabilities of MSCs have been under extensive investigation for practical application. Regarding therapy, the efficacy usually depends on the amount of MSCs. Nevertheless, the yield of MSCs is still limited due to the traditional cultural methods. Herein, we proposed a three-dimensional (3D) scaffold prepared using poly lactic-co-glycolic acid (PLGA) nanofiber with polylysine (PLL) grafting, to promote the growth and proliferation of MSCs derived from the human umbilical cord (hUC-MSCs). We found that the inoculated hUC-MSCs adhered efficiently to the PLGA scaffold with good affinity, fast growth rate, and good multipotency. The harvested cells were ideally distributed on the scaffold and we were able to gain a larger yield than the traditional culturing methods under the same condition. Thus, our cell seeding with a 3D scaffold could serve as a promising strategy for cell proliferation in the large-scale production of MSCs. Moreover, the simplicity and low preparation cost allow this 3D scaffold to extend its potential application beyond cell culture. Supplementary Information: The online version contains supplementary material available at 10.1186/s40643-023-00635-6.

Natural variation of Alfin-like family affects seed size and drought tolerance in rice.

The Alfin-like (AL) family is a group of small plant-specific transcriptional factors involved in abiotic stresses in dicotyledon. In an early study, we found an AL gene in rice that was associated with grain yield under drought stress. However, little information is known about the AL family in rice. In this study, AL genes in the rice genome were identified, and the OsAL proteins were found to locate in the nucleus and have no transcriptional self-activation activity. The expression of the OsALs was regulated by different environmental stimulations and plant hormones. Association and domestication analysis revealed that natural variation of most OsALs was significantly associated with yield traits, drought resistance and divergence in grain size in indica and japonica rice varieties. Hap1 of OsAL7.1 and Hap7 of OsAL11 were favorable haplotypes of seed weight and germination under osmotic stress. Furthermore, osal7.1 and osal11 mutants have larger seeds and are more sensitive to abscisic acid and mannitol during germination stage. Overexpressing of OsAL7.1 and OsAL11 in rice weakened the tolerance to drought in the adult stage. Thus, our work provides informative knowledge for exploring and harnessing haplotype diversity of OsALs to improve yield stability under drought stress.

Pre-mRNA processing factor 19 functions in DNA damage repair and radioresistance by modulating cyclin D1 in hepatocellular carcinoma.

Pre-mRNA processing factor 19 (PRP19) is elevated in hepatocellular carcinoma (HCC); however, little is known about its function in DNA damage repair in HCC. In this study, analysis of The Cancer Genome Atlas data and our tumor models after ionizing radiation (IR) treatment indicated that increased expression of PRP19 was positively correlated with DNA damage repair. Gain of PRP19 expression induced by plasmids resulted in decreases in apoptosis and double-strand breaks (DSBs), and an increase in cell survival after IR. Loss of PRP19 expression induced by small interfering RNAs resulted in the accumulation of apoptosis and DSBs, and a decrease in cell survival. Mechanistically, the effect of PRP19 on DNA damage repair was mediated by the modulation of cyclin D1 expression in HCC. PRP19 controlled the translation of cyclin D1 by modulating eukaryotic initiation factor 4E. PRP19 affected the DNA damage repair ability of cyclin D1 by interacting with the WD40 domain. The combination of PRP19 and cyclin D1 was more valuable than each single marker for predicting the prognosis of patients. Taken together, the present results demonstrate that PRP19 promotes DNA damage repair by modulating cyclin D1 expression and function, thereby contributing to the radioresistance in HCC.

The Mixed Opioid Receptor Antagonist Naltrexone Mitigates Stimulant-Induced Euphoria: A Double-Blind, Placebo-Controlled Trial of Naltrexone.

OBJECTIVE: Supratherapeutic doses of methylphenidate activate µ-opioid receptors, which are linked to euphoria. This study assessed whether naltrexone, a mixed µ-opioid antagonist, may attenuate the euphoric effects of stimulants, thereby minimizing their abuse potential in subjects with attention-deficit/hyperactivity disorder (ADHD). METHODS: We conducted a 6-week, double-blind, placebo-controlled, randomized clinical trial of naltrexone in adults with DSM-IV ADHD receiving open treatment with a long-acting formulation of methylphenidate (January 2013 to June 2015). Spheroidal Oral Drug Absorption System methylphenidate (SODAS-MPH) was administered twice daily, was titrated to ~1 mg/kg/d over 3 weeks, and was continued for 3 additional weeks depending on response and adverse effects. Subjects were adults with ADHD preselected for having experienced euphoria with an oral test dose of 60 mg of immediate-release methylphenidate (IR-MPH). The primary outcome measure was Question 2 (Liking a Drug Effect) on the Drug Rating Questionnaire, Subject version, which was assessed after oral test doses of 60 mg of IR-MPH were administered after the third and sixth weeks of treatment with SODAS-MPH. RESULTS: Thirty-seven subjects who experienced stimulant-induced (mild) euphoria at a baseline visit were started in the open trial of SODAS-MPH and randomized to naltrexone 50 mg/d or placebo. Thirty-one subjects completed through week 3, and 25 completed through week 6. Naltrexone significantly diminished the euphoric effect of IR-MPH during the heightened-risk titration phase (primary outcome; first 3 weeks) (χ² = 5.07, P = .02) but not the maintenance phase (weeks 4-6) (χ² = 0.22, P = .64) of SODAS-MPH treatment. CONCLUSIONS: Preclinical findings are extended to humans showing that naltrexone may mitigate stimulant-associated euphoria. Our findings provide support for further studies combining opioid receptor antagonists with stimulants to reduce abuse potential. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01673594.

Opiate Antagonists Do Not Interfere With the Clinical Benefits of Stimulants in ADHD: A Double-Blind, Placebo-Controlled Trial of the Mixed Opioid Receptor Antagonist Naltrexone.

OBJECTIVE: Methylphenidate activates µ-opioid receptors, which are linked to euphoria. µ-Opioid antagonists, such as naltrexone, may attenuate the euphoric effects of stimulants, thereby minimizing their abuse potential. This study assessed whether the combination of naltrexone with methylphenidate is well-tolerated while preserving the clinical benefits of stimulants in subjects with attention-deficit/hyperactivity disorder (ADHD). METHODS: We conducted a 6-week, double-blind, placebo-controlled, randomized clinical trial of naltrexone in adults with DSM-IV ADHD receiving open treatment with a long-acting formulation of methylphenidate from January 2013 to July 2015. Spheroidal Oral Drug Absorption System (SODAS) methylphenidate was administered twice daily, was titrated to approximately 1 mg/kg/d over 3 weeks, and was continued for 3 additional weeks depending on response and adverse effects. Subjects were adults with ADHD preselected for having experienced euphoria with a test dose of immediate-release methylphenidate. The primary outcome measure was the Adult ADHD Investigator Symptom Report Scale (AISRS). RESULTS: Thirty-seven subjects who experienced stimulant-induced (mild) euphoria at a baseline visit were started in the open trial of SODAS methylphenidate and randomly assigned to naltrexone 50 mg or placebo. Thirty-one subjects completed the study through week 3, and 25 completed through week 6. Throughout 6 weeks of blinded naltrexone and open methylphenidate treatment, the coadministration of naltrexone with methylphenidate did not interfere with the clinical effectiveness of methylphenidate for ADHD symptoms. Additionally, the combination of naltrexone and methylphenidate did not produce an increase in adverse events compared with methylphenidate alone. CONCLUSIONS: Our findings provide support for the concept of combining opioid receptor antagonists with stimulants to provide an effective stimulant formulation with less abuse potential. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01673594​.

A prenatal nicotine exposure mouse model of methylphenidate responsive ADHD-associated cognitive phenotypes.

Prenatal exposure to nicotine via cigarette smoke or other forms of tobacco use is a significant environmental risk factor for attention deficit hyperactivity disorder (ADHD). The neurobiological mechanisms underlying the link between prenatal nicotine exposure (PNE) and ADHD are not well understood. Animal models, especially rodent models, are beginning to bridge this gap in knowledge. Although ADHD is characterized by hyperactivity, inattention, impulsivity and working memory deficits, the majority of the animal models are based on only one or two ADHD associated phenotypes, in particular, hyperactivity or inattention. We report a PNE mouse model that displays the full range of ADHD associated behavioral phenotypes including working memory deficit, attention deficit and impulsive-like behavior. All of the ADHD-associated phenotypes respond to a single administration of a therapeutic equivalent dose of methylphenidate. In an earlier study, we showed that PNE produces hyperactivity, frontal cortical hypodopaminergic state and thinning of the cingulate cortex. Collectively, these data suggest that the PNE mouse model recapitulates key features of ADHD and may be a suitable preclinical model for ADHD research.

Transgenerational transmission of hyperactivity in a mouse model of ADHD.

Attention deficit hyperactivity disorder (ADHD) is a neurobehavioral disorder affecting children and adults. Genetic and environmental factors are associated with the etiology of ADHD. Among the environmental factors, exposure of the developing brain to nicotine is considered a major risk factor. Recent evidence suggests that environmental influences on the brain and behavior may be transmitted from one generation to the next. We used a prenatal nicotine exposure (PNE) mouse model of ADHD to test the hypothesis that PNE-induced hyperactivity, a proxy for human ADHD phenotype, is transmitted from one generation to the next. Our data reveal transgenerational transmission of PNE-induced hyperactivity in mice via the maternal but not the paternal line of descent. We suggest that transgenerational transmission is a plausible mechanism for propagation of environmentally induced ADHD phenotypes in the population.

Is ADHD a risk for posttraumatic stress disorder (PTSD)? Results from a large longitudinal study of referred children with and without ADHD.

OBJECTIVES: Preclinical studies link prenatal nicotine exposure with the development of both ADHD-like phenotype in rodents and blockade of extinction learning in a fear conditioning paradigm, a preclinical model of posttraumatic stress disorder (PTSD). While these findings suggest that either ADHD, prenatal nicotine exposure, or both could be a risk factor for PTSD, such associations have not been investigated in humans. METHODS: Subjects were ascertained from family-genetic, longitudinal studies of paediatrically and psychiatrically referred children with and without ADHD of both sexes and their siblings followed for 10 years from childhood into adulthood (n = 403 probands; n = 464 siblings; mean age at follow-up of probands and siblings = 22.0 years). All subjects were comprehensively evaluated with structured diagnostic interviews that included questions regarding prenatal use of cigarettes. RESULTS: A total of 12% (104/867) of the sample had been exposed to maternal smoking during pregnancy. There was no interaction effect between maternal smoking during pregnancy and ADHD (z = 0.01, P = 0.99). Maternal smoking during pregnancy and ADHD were independent, significant risk factors for PTSD at the 10-year follow-up (odds ratio = 3.58 [1.35,9.48], z = 2.57, P = 0.01 and odds ratio = 2.23 [1.06,4.69], z = 2.11, P = 0.04, respectively). CONCLUSIONS: These results suggest that both maternal smoking during pregnancy and ADHD are significant predictors of PTSD in humans.

Prenatal nicotine exposure mouse model showing hyperactivity, reduced cingulate cortex volume, reduced dopamine turnover, and responsiveness to oral methylphenidate treatment.

Cigarette smoking, nicotine replacement therapy, and smokeless tobacco use during pregnancy are associated with cognitive disabilities later in life in children exposed prenatally to nicotine. The disabilities include attention deficit hyperactivity disorder (ADHD) and conduct disorder. However, the structural and neurochemical bases of these cognitive deficits remain unclear. Using a mouse model we show that prenatal nicotine exposure produces hyperactivity, selective decreases in cingulate cortical volume, and radial thickness, as well as decreased dopamine turnover in the frontal cortex. The hyperactivity occurs in both male and female offspring and peaks during the "active" or dark phase of the light/dark cycle. These features of the mouse model closely parallel the human ADHD phenotype, whether or not the ADHD is associated with prenatal nicotine exposure. A single oral, but not intraperitoneal, administration of a therapeutic equivalent dose (0.75 mg/kg) of methylphenidate decreases the hyperactivity and increases the dopamine turnover in the frontal cortex of the prenatally nicotine exposed mice, once again paralleling the therapeutic effects of this compound in ADHD subjects. Collectively, our data suggest that the prenatal nicotine exposure mouse model has striking parallels to the ADHD phenotype not only in behavioral, neuroanatomical, and neurochemical features, but also with respect to responsiveness of the behavioral phenotype to methylphenidate treatment. The behavioral, neurochemical, and anatomical biomarkers in the mouse model could be valuable for evaluating new therapies for ADHD and mechanistic investigations into its etiology.

Methylphenidate and µ opioid receptor interactions: a pharmacological target for prevention of stimulant abuse.

Methylphenidate (MPH) is one of the most commonly used and highly effective treatments for attention deficit hyperactivity disorder (ADHD) in children and adults. As the therapeutic use of MPH has increased, so has its abuse and illicit street-use. Yet, the mechanisms associated with development of MPH-associated abuse and dependence are not well understood making it difficult to develop methods to help its mitigation. As a result, many ADHD patients especially children and youth, that could benefit from MPH treatment do not receive it and risk lifelong disabilities associated with untreated ADHD. Therefore, understanding the mechanisms associated with development of MPH addiction and designing methods to prevent it assume high public health significance. Using a mouse model we show that supra-therapeutic doses of MPH produce rewarding effects (surrogate measure for addiction in humans) in a conditioned place preference paradigm and upregulate µ opioid receptor (MOPR) activity in the striatum and nucleus accumbens, brain regions associated with reward circuitry. Co-administration of naltrexone, a non-selective opioid receptor antagonist, prevents MPH-induced MOPR activation and the rewarding effects. The MPH-induced MOPR activation and rewarding effect require activation of the dopamine D1 but not the D2-receptor. These findings identify the MOPR as a potential target for attenuating rewarding effects of MPH and suggest that a formulation that combines naltrexone with MPH could be a useful pharmaceutical approach to alleviate abuse potential of MPH and other stimulants.

Bioluminescence imaging reveals inhibition of tumor cell proliferation by Alzheimer's amyloid beta protein.

BACKGROUND: Cancer and Alzheimer's disease (AD) are two seemingly distinct diseases and rarely occur simultaneously in patients. To explore molecular determinants differentiating pathogenic routes towards AD or cancer, we investigate the role of amyloid beta protein (Abeta) on multiple tumor cell lines that are stably expressing luciferase (human glioblastoma U87; human breast adenocarcinoma MDA-MB231; and mouse melanoma B16F). RESULTS: Quantification of the photons emitted from the MDA-MB231 or B16F cells revealed a significant inhibition of cell proliferation by the conditioning media (CM) derived from amyloid precursor protein (APP) over-expressing cells. The inhibition of U87 cells was observed only after the media was conditioned for longer than 2 days with APP over-expressing cells. CONCLUSION: Our results suggest that Abeta plays an inhibitory role in tumor cell proliferation; this effect could depend on the type of tumor cells and amount of Abeta.

Workflow and methods of high-content time-lapse analysis for quantifying intracellular calcium signals.

Calcium ions (Ca2+) play a fundamental role in a variety of physiological functions in many cell types by acting as a secondary messenger. Variation of intracellular Ca2+ concentration ([Ca2+]i) is often observed when the cell is stimulated. However, it is a challenging task to automatically quantify intracellular [Ca2+]i in a population of cells. In this study, we present a workflow including specific algorithms for the automated intracellular calcium signal analysis using high-content, time-lapse cellular images. The experimental validations indicate the effectiveness of the proposed workflow and algorithms. We applied the workflow to analyze the intracellular calcium signals induced by different concentrations of H2O2 in the cell lines transfected by presenilin-1 (PS-1) that is known to be closely related to the familial Alzheimer's disease (FAD). The analysis results imply an important role of mutant PS-1, but not normal human PS-1 and mutant human amyloid precursor protein (APP), in enhancing intracellular calcium signaling induced by H2O2.

Comparison of reversible-jump Markov-chain-Monte-Carlo learning approach with other methods for missing enzyme identification.

Computational identification of missing enzymes plays a significant role in accurate and complete reconstruction of metabolic network for both newly sequenced and well-studied organisms. For a metabolic reaction, given a set of candidate enzymes identified according to certain biological evidences, a powerful mathematical model is required to predict the actual enzyme(s) catalyzing the reactions. In this study, several plausible predictive methods are considered for the classification problem in missing enzyme identification, and comparisons are performed with an aim to identify a method with better performance than the Bayesian model used in previous work. In particular, a regression model consisting of a linear term and a nonlinear term is proposed to apply to the problem, in which the reversible jump Markov-chain-Monte-Carlo (MCMC) learning technique (developed in [Andrieu C, Freitas Nando de, Doucet A. Robust full Bayesian learning for radial basis networks 2001;13:2359-407.]) is adopted to estimate the model order and the parameters. We evaluated the models using known reactions in Escherichia coli, Mycobacterium tuberculosis, Vibrio cholerae and Caulobacter cresentus bacteria, as well as one eukaryotic organism, Saccharomyces Cerevisiae. Although support vector regression also exhibits comparable performance in this application, it was demonstrated that the proposed model achieves favorable prediction performance, particularly sensitivity, compared with the Bayesian method.

High content image analysis for human H4 neuroglioma cells exposed to CuO nanoparticles.

BACKGROUND: High content screening (HCS)-based image analysis is becoming an important and widely used research tool. Capitalizing this technology, ample cellular information can be extracted from the high content cellular images. In this study, an automated, reliable and quantitative cellular image analysis system developed in house has been employed to quantify the toxic responses of human H4 neuroglioma cells exposed to metal oxide nanoparticles. This system has been proved to be an essential tool in our study. RESULTS: The cellular images of H4 neuroglioma cells exposed to different concentrations of CuO nanoparticles were sampled using IN Cell Analyzer 1000. A fully automated cellular image analysis system has been developed to perform the image analysis for cell viability. A multiple adaptive thresholding method was used to classify the pixels of the nuclei image into three classes: bright nuclei, dark nuclei, and background. During the development of our image analysis methodology, we have achieved the followings: (1) The Gaussian filtering with proper scale has been applied to the cellular images for generation of a local intensity maximum inside each nucleus; (2) a novel local intensity maxima detection method based on the gradient vector field has been established; and (3) a statistical model based splitting method was proposed to overcome the under segmentation problem. Computational results indicate that 95.9% nuclei can be detected and segmented correctly by the proposed image analysis system. CONCLUSION: The proposed automated image analysis system can effectively segment the images of human H4 neuroglioma cells exposed to CuO nanoparticles. The computational results confirmed our biological finding that human H4 neuroglioma cells had a dose-dependent toxic response to the insult of CuO nanoparticles.

A novel computational approach for automatic dendrite spines detection in two-photon laser scan microscopy.

BACKGROUND: Recent research has shown that there is a strong correlation between the functional properties of a neuron and its morphologic structure. Current morphologic analyses typically involve a significant component of computer-assisted manual labor, which is very time-consuming and is susceptible to operator bias. The existing semi-automatic approaches largely reduce user efforts. However, some manual interventions, such as setting a global threshold for segmentation, are still needed during image processing. METHODS: We present an automated approach, which can greatly help neurobiologists obtain quantitative morphological information about a neuron and its spines. The automation includes an adaptive thresholding method, which can yield better segment results than the prevalent global thresholding method. It also introduces an efficient backbone extraction method, a SNR based, detached spine component detection method, and an attached spine component detection method based on the estimation of local dendrite morphology. RESULTS: The morphology information obtained both manually and automatically are compared in detail. Using the Kolmogov-Smirnov test, we find a 99.13% probability that the dendrite length distributions are the same for the automatic and manual processing methods. The spine detection results are also compared with other existing semi-automatic approaches. The comparison results show that our approach has 33% fewer false positives and 77% fewer false negatives on average. CONCLUSIONS: Because the proposed detection algorithm requires less user input and performs better than existing algorithms, our approach can quickly and accurately process neuron images without user intervention.

Mutual information-based feature selection in studying perturbation of dendritic structure caused by TSC2 inactivation.

In this study, the effect of protein Tuberous sclerosis 2 (TSC2) on the dendritic spine density and length was demonstrated by using TSC2-RNAinactivation. In addition, the role of rapamycin, an antagonist of the molecular target of rapamycin, in the morphological changes of spine caused by TSC2 silencing was investigated. The features were extracted from highresolution three-dimensional image stacks collected by two-photon laser scanning microscopy of green fluorescing pyramidal cells expressing TSC2-RNA interference (RNAi), or TSC2-RNAi and rapamycin treatment in rat hippocampal slice cultures. We proposed to apply the lognormal distribution method for feature extraction. The extracted features of three cases under investigation, namely, (1) green-fluorescent protein GFP vs TSC2-RNAi, (2) GFP vs TSC2-RNAi and rapamycin, and (3) TSC2-RNAi vs TSC2-RNAi and rapamycin, were analyzed by mutual information-based feature selection and evaluated by three classifiers, K-nearest neighbor, Perceptron, and two-layer neural networks. The results showed that both the spine density and length have significant morphological changes after TSC2-RNAi treatment. However, rapamycin treatment could reverse the effect of TSC2-RNAi on spine length but not on spine density. These results are consistent with the results reported in the scientific literature. Finally, we explored the application of pattern recognition method in a small sample with richer feature properties, namely bootstrap mutual information estimation and a mutual information- based feature selection method.

Computerized image analysis for quantitative neuronal phenotyping in zebrafish.

An integrated microscope image analysis pipeline is developed for automatic analysis and quantification of phenotypes in zebrafish with altered expression of Alzheimer's disease (AD)-linked genes. We hypothesize that a slight impairment of neuronal integrity in a large number of zebrafish carrying the mutant genotype can be detected through the computerized image analysis method. Key functionalities of our zebrafish image processing pipeline include quantification of neuron loss in zebrafish embryos due to knockdown of AD-linked genes, automatic detection of defective somites, and quantitative measurement of gene expression levels in zebrafish with altered expression of AD-linked genes or treatment with a chemical compound. These quantitative measurements enable the archival of analyzed results and relevant meta-data. The structured database is organized for statistical analysis and data modeling to better understand neuronal integrity and phenotypic changes of zebrafish under different perturbations. Our results show that the computerized analysis is comparable to manual counting with equivalent accuracy and improved efficacy and consistency. Development of such an automated data analysis pipeline represents a significant step forward to achieve accurate and reproducible quantification of neuronal phenotypes in large scale or high-throughput zebrafish imaging studies.