The Adoption of Semidwarf Spring Wheat and the Associated Nitrous Oxide Effects in Saskatchewan

After the Green Revolution, semidwarf varieties of wheat increased in popularity worldwide. With an increase in lodging resistance and higher responsiveness to nitrogen, farmers have the ability to apply more nitrogen to achieve higher yields. However, while semidwarf varieties are favorable to farmers seeking to increase productivity, the net change in greenhouse gas emissions resulting from the increased use of nitrogen fertilizer remains underexplored. This thesis studies the joint determination of semidwarf variety selection and nitrogen use in Saskatchewan, Canada—one of the leading provinces in wheat production. We develop a Control Function (CF) model to estimate the joint choices of semidwarf wheat varieties and nitrogen application rates using field-level data of Saskatchewan farms between 2011 and 2019. After that, we employ emission factors from the literature to estimate changes in direct nitrous oxide (N2O) emissions when farmers adopt semidwarf wheat and subsequently change nitrogen rates. Our regres- sion model suggests a 5.9% expected increase in nitrogen application rate when a farmer switches from conventional to semidwarf wheat. The subsequent analysis suggests that although semidwarf wheat generally has higher nitrogen application rates than conventional wheat, their fertilizer-induced direct N2O emissions per tonne of grain production are fairly similar. Based on the adoption status of semidwarf wheat and conventional wheat in 2019, if all conventional wheat acres in Saskatchewan switch to semidwarf wheat, the value of environmental damage associated with the direct N2O emissions induced by nitrogen fertilizer applied to Saskatchewan spring wheat would increase by at least $0.29 millions of CAD

A Preliminary Study of DBH (Encoding Dopamine Beta-Hydroxylase) Genetic Variation and Neural Correlates of Emotional and Motivational Processing in Individuals With and Without Pathological Gambling

Background and aims Corticostriatal-limbic neurocircuitry, emotional and motivational processing, dopaminergic and noradrenergic systems and genetic factors have all been implicated in pathological gambling (PG). However, allelic variants of genes influencing dopaminergic and noradrenergic neurotransmitters have not been investigated with respect to the neural correlates of emotional and motivational states in PG. Dopamine beta-hydroxylase (DBH) converts dopamine to norepinephrine; the T allele of a functional single-nucleotide polymorphism rs1611115 (C-1021T) in the DBH gene is associated with less DBH activity and has been linked to emotional processes and addiction. Here, we investigate the influence of rs1611115 on the neural correlates of emotional and motivational processing in PG and healthy comparison (HC) participants. Methods While undergoing functional magnetic resonance imaging, 18 PG and 25 HC participants, all European Americans, viewed gambling-, sad-, and cocaine-related videotapes. Analyses focused on brain activation differences related to DBH genotype (CC/T-carrier [i.e., CT and TT]) and condition (sad/gambling/cocaine). Results CC participants demonstrated greater recruitment of corticostriatal-limbic regions, relative to T-carriers. DBH variants were also associated with altered corticostriatal-limbic activations across the different videotape conditions, and this association appeared to be driven by greater activation in CC participants relative to T-carriers during the sad condition. CC relative to T-carrier subjects also reported greater subjective sadness to the sad videotapes. Conclusions Individual differences in genetic composition linked to aminergic function contribute significantly to emotional regulation across diagnostic groups and warrant further investigation in PG

Spiritual Experiences are Related to Engagement of a Ventral Frontotemporal Functional Brain Network: Implications for Prevention and Treatment of Behavioral and Substance Addictions

Background and aims: Spirituality is an important component of 12-step programs for behavioral and substance addictions and has been linked to recovery processes. Understanding the neural correlates of spiritual experiences may help to promote efforts to enhance recovery processes in behavioral addictions. We recently used general linear model (GLM) analyses of functional magnetic resonance imaging data to examine neural correlates of spiritual experiences, with findings implicating cortical and subcortical brain regions. Although informative, the GLM-based approach does not provide insight into brain circuits that may underlie spiritual experiences. Methods: Spatial independent component analysis (sICA) was used to identify functional brain networks specifically linked to spiritual (vs. stressful or neutral-relaxing) conditions using a previously validated guided imagery task in 27 young adults. Results: Using sICA, engagement of a ventral frontotemporal network was identified that was engaged at the onset and conclusion of the spiritual condition in a manner distinct from engagement during the stress or neutral-relaxing conditions. Degree of engagement correlated with subjective reports of spirituality in the scanner (r = .71, p < .001) and an out-of-the-magnet measure of spirituality (r = .48, p < .018). Discussion and conclusion: The current findings suggest a distributed functional neural network associated with spiritual experiences and provide a foundation for investigating brain mechanisms underlying the role of spirituality in recovery from behavioral addictions

Systemic immune effects of anesthetics and their intracellular targets in tumors

According to the result released by the World Health Organization (WHO), non-communicable diseases have occupied four of the top 10 current causes for death in the world. Cancer is one of the significant factors that trigger complications and deaths; more than 80% cancer patients require surgical or palliative treatment. In this case, anesthetic treatment is indispensable. Since cancer is a heterogeneous disease, various types of interventions can activate oncogenes or mutate tumor suppressor genes. More and more researchers believe that anesthetics have a certain effect on the long-term recurrence and metastasis of tumors, but it is still controversial whether they promote or inhibit the progression of cancer. On this basis, a series of retrospective or prospective randomized clinical trials have been conducted, but it seems to be difficult to reach a conclusion within 5 years or longer. This article focuses on the effects of anesthetic drugs on immune function and cancer and reviews their latest targets on the tumor cells, in order to provide a theoretical basis for optimizing the selection of anesthetic drugs, exploring therapeutic targets, and improving the prognosis of cancer patients

Medicarpin induces G1 arrest and mitochondria-mediated intrinsic apoptotic pathway in bladder cancer cells

Bladder cancer (BC) is the tenth most commonly diagnosed cancer. High recurrence, chemoresistance, and low response rate hinder the effective treatment of BC. Hence, a novel therapeutic strategy in the clinical management of BC is urgently needed. Medicarpin (MED), an isoflavone from Dalbergia odorifera, can promote bone mass gain and kill tumor cells, but its anti-BC effect remains obscure. This study revealed that MED effectively inhibited the proliferation and arrested the cell cycle at the G1 phase of BC cell lines T24 and EJ-1 in vitro. In addition, MED could significantly suppress the tumor growth of BC cells in vivo. Mechanically, MED induced cell apoptosis by upregulating pro-apoptotic proteins BAK1, Bcl2-L-11, and caspase-3. Our data suggest that MED suppresses BC cell growth in vitro and in vivo via regulating mitochondria-mediated intrinsic apoptotic pathways, which can serve as a promising candidate for BC therapy

Artificial Intelligence Framework Identifies Candidate Targets for Drug Repurposing in Alzheimer’s Disease

Background: Genome-wide association studies (GWAS) have identified numerous susceptibility loci for Alzheimer’s disease (AD). However, utilizing GWAS and multi-omics data to identify high-confidence AD risk genes (ARGs) and druggable targets that can guide development of new therapeutics for patients suffering from AD has heretofore not been successful. Methods: To address this critical problem in the field, we have developed a network-based artificial intelligence framework that is capable of integrating multi-omics data along with human protein–protein interactome networks to accurately infer accurate drug targets impacted by GWAS-identified variants to identify new therapeutics. When applied to AD, this approach integrates GWAS findings, multi-omics data from brain samples of AD patients and AD transgenic animal models, drug-target networks, and the human protein–protein interactome, along with large-scale patient database validation and in vitro mechanistic observations in human microglia cells. Results: Through this approach, we identified 103 ARGs validated by various levels of pathobiological evidence in AD. Via network-based prediction and population-based validation, we then showed that three drugs (pioglitazone, febuxostat, and atenolol) are significantly associated with decreased risk of AD compared with matched control populations. Pioglitazone usage is significantly associated with decreased risk of AD (hazard ratio (HR) = 0.916, 95% confidence interval [CI] 0.861–0.974, P = 0.005) in a retrospective case-control validation. Pioglitazone is a peroxisome proliferator-activated receptor (PPAR) agonist used to treat type 2 diabetes, and propensity score matching cohort studies confirmed its association with reduced risk of AD in comparison to glipizide (HR = 0.921, 95% CI 0.862–0.984, P = 0.0159), an insulin secretagogue that is also used to treat type 2 diabetes. In vitro experiments showed that pioglitazone downregulated glycogen synthase kinase 3 beta (GSK3β) and cyclin-dependent kinase (CDK5) in human microglia cells, supporting a possible mechanism-of-action for its beneficial effect in AD. Conclusions: In summary, we present an integrated, network-based artificial intelligence methodology to rapidly translate GWAS findings and multi-omics data to genotype-informed therapeutic discovery in AD

Aberrant Expression Profiles of lncRNAs and Their Associated Nearby Coding Genes in the Hippocampus of the SAMP8 Mouse Model with AD

The senescence-accelerated mouse prone 8 (SAMP8) mouse model is a useful model for investigating the fundamental mechanisms involved in the age-related learning and memory deficits of Alzheimer's disease (AD), while the SAM/resistant 1 (SAMR1) mouse model shows normal features. Recent evidence has shown that long non-coding RNAs (lncRNAs) may play an important role in AD pathogenesis. However, a comprehensive and systematic understanding of the function of AD-related lncRNAs and their associated nearby coding genes in AD is still lacking. In this study, we collected the hippocampus, the main area of AD pathological processes, of SAMP8 and SAMR1 animals and performed microarray analysis to identify aberrantly expressed lncRNAs and their associated nearby coding genes, which may contribute to AD pathogenesis. We identified 3,112 differentially expressed lncRNAs and 3,191 differentially expressed mRNAs in SAMP8 mice compared to SAMR1 mice. More than 70% of the deregulated lncRNAs were intergenic and exon sense-overlapping lncRNAs. Gene Ontology (GO) and pathway analyses of the AD-related transcripts were also performed and are described in detail, which imply that metabolic process reprograming was likely related to AD. Furthermore, six lncRNAs and six mRNAs were selected for further validation of the microarray results using quantitative PCR, and the results were consistent with the findings from the microarray. Moreover, we analyzed 780 lincRNAs (also called long "intergenic" non-coding RNAs) and their associated nearby coding genes. Among these lincRNAs, AK158400 had the most genes nearby (n = 13), all of which belonged to the histone cluster 1 family, suggesting regulation of the nucleosome structure of the chromosomal fiber by affecting nearby genes during AD progression. In addition, we also identified 97 aberrant antisense lncRNAs and their associated coding genes. It is likely that these dysregulated lncRNAs and their associated nearby coding genes play a role in the development and/or progression of AD

Aspect of Clusters Correlation at Light Nuclei Excited State

The correlation of $\alpha\alpha$ was probed via measuring the transverse momentum $p_{T}$ and width $\delta p_{T}$ of one $\alpha$, for the first time, which represents the spatial and dynamical essentialities of the initial coupling state in $^{8}$Be nucleus. The weighted interaction vertex of 3$\alpha$ reflected by the magnitudes of their relative momentums and relative emission angles proves the isosceles triangle configuration for 3$\alpha$ at the high excited energy analogous Hoyle states.Comment: 8 pages, 9 figure