Search

Ketamine has rapid and sustained antidepressant effects in patients with treatment-resistant depression (TRD). However, the underlying mechanisms of action are not well understood. There is increasing evidence that TRD is associated with a pro-inflammatory state and that ketamine may inhibit inflammatory processes. We thus investigated whole blood transcriptional profiles related to TRD and gene expression changes associated with treatment response to ketamine. Whole blood was collected at baseline (21 healthy controls [HC], 26 patients with TRD) and then again in patients with TRD 24 hours following a single intravenous infusion of ketamine (0.5 mg/kg). We performed RNA-sequencing and analyzed (a) baseline transcriptional profiles between patients with TRD and HC, (b) responders vs. non-responders before ketamine treatment, and (c) gene expression signatures associated with clinical improvement. At baseline, patients with TRD compared to HC showed a gene expression signature indicative of interferon signaling pathway activation. Prior to ketamine administration, the metabotropic glutamate receptor gene GRM2 and the ionotropic glutamate receptor gene GRIN2D were upregulated in responders compared to non-responders. Response to ketamine was associated with a distinct transcriptional signature, however, we did not observe gene expression changes indicative of an anti-inflammatory effect. Future studies are needed to determine the role of the peripheral immune system in the antidepressant effect of ketamine.

Autism spectrum disorder (ASD) is a serious neurodevelopmental disorder with a very high prevalence rate and a chronic disease course beginning in early childhood. Despite the tremendous burden of ASD, there are currently no disease-modifying treatments. Like many neuropsychiatric illnesses ASD has a complex pathophysiology driven by genetic and environmental factors. There is interest in identifying modifiable environmental factors as potential translational research strategies for development of therapeutics for ASD. A rapidly growing body of research demonstrates that the resident bacteria of the gastrointestinal tract, collectively the gut microbiome, have profound influence on brain and behavior. This gut-brain signaling pathway is highly relevant to ASD as the microbiome begins to form at birth, is heavily influenced by environmental factors throughout early life, and begins to stabilize at the same stage of development that symptoms of ASD begin to develop. To investigate potential gene x microbiome interactions in a model of ASD, we utilized mutant mice carrying a deletion of the ASD-associated Shank3 gene (Shank3KO), which clinically manifests as Phelan-McDermid syndrome, as a model for genetic risk of ASD. Analysis of the gut microbiome of Shank3KO mice demonstrated genotype effects on both microbiome composition and metabolite production. Behaviorally, Shank3KO mice demonstrate decreased social interactions and have altered anxiety and compulsive-like behaviors. Disruption of the microbiome with broad spectrum antibiotics lead to an exacerbation of all behavioral phenotypes in Shank3KO mice. Additionally, we found that Shank3KO mice had markedly increased changes in gene expression in the prefrontal cortex following microbiome depletion. Taken together, our results suggest a gene x microbiome interaction in this mouse model for ASD and raise the possibility that targeting the microbiome may be a valid translational research strategy in developing therapeutics for ASD.

Despite being one of the most significant economic contributors of the country, Canada’s construction industry is lagging behind other sectors when it comes to labor productivity improvements. The construction industry is very collaborative as a general contractor, will hire trade contractors to perform most of a project’s work; meaning low productivity from one contractor can have a domino effect on the shared success of a project. To address this issue and encourage trade contractors to improve their productivity tracking methods, an investigative study was done on the productivity views and tracking methods of various trade contractors. Additionally, an in-depth review was done on four standard tracking methods used in the construction industry: cost codes, benchmarking, the job productivity measurement (JPM) standard, and WorkFace Planning (WFP). The four tracking methods were used as a baseline in comparing the trade contractors’ responses, determining gaps within their current tracking methods, and for making improvement recommendations. 15 interviews were conducted with different trades to analyze how contractors value productivity. The results of these analyses indicated that there seem to be gaps within the construction industry when it comes to an understanding of the purpose and value in productivity tracking. The trade contractors also shared their current productivity tracking systems; which were then compared to the four standard tracking methods used in the construction industry. Gaps were identified in their various tracking methods and using a framework; recommendations were made based on the type of trade on how to improve how they track productivity.

Previous studies have demonstrated that independent stimulation of either electron transport or RuBP regeneration can increase the rate of photosynthetic carbon assimilation and plant biomass. In this paper, we present evidence that a multi-gene approach to simultaneously manipulate these two processes provides a further stimulation of photosynthesis. We report on the introduction of the cyanobacterial bifunctional enzyme fructose-1,6-bisphosphatase/sedoheptulose-1,7-bisphosphatase or overexpression of the plant enzyme sedoheptulose-1,7-bisphosphatase, together with expression of the red algal protein cytochromec6, and show that a further increase in biomass accumulation under both glasshouse and field conditions can be achieved. Furthermore, we provide evidence that the simultaneous stimulation of electron transport and RuBP regeneration can lead to enhanced intrinsic water use efficiency under field conditions.One sentence summarySimultaneous stimulation of RuBP regeneration and electron transport results in improvements in biomass yield in glasshouse and field grown tobacco.

Background: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk is needed to plan management. Objectives: To assess the performance of existing pre-eclampsia prediction models and to develop and validate models for pre-eclampsia using individual participant data meta-analysis. We also estimated the prognostic value of individual markers. Design: This was an individual participant data meta-analysis of cohort studies. Setting: Source data from secondary and tertiary care. Predictors: We identified predictors from systematic reviews, and prioritised for importance in an international survey. Primary outcomes: Early-onset (delivery at < 34 weeks’ gestation), late-onset (delivery at ≥ 34 weeks’ gestation) and any-onset pre-eclampsia. Analysis: We externally validated existing prediction models in UK cohorts and reported their performance in terms of discrimination and calibration.We developed and validated 12 new models based on clinical characteristics, clinical characteristics and biochemical markers, and clinical characteristics and ultrasound markers in the first and second trimesters. We summarised the data set-specific performance of each model using a random-effects meta-analysis. Discrimination was considered promising for C-statistics of ≥ 0.7, and calibration was considered good if the slope was near 1 and calibration-in-the-large was near 0. Heterogeneity was quantified using I2 and 2. A decision curve analysis was undertaken to determine the clinical utility (net benefit) of the models. We reported the unadjusted prognostic value of individual predictors for pre-eclampsia as odds ratios with 95% confidence and prediction intervals. Results: The International Prediction of Pregnancy Complications network comprised 78 studies (3,570,993 singleton pregnancies) identified from systematic reviews of tests to predict pre-eclampsia. Twenty-four of the 131 published prediction models could be validated in 11 UK cohorts. Summary C-statistics were between 0.6 and 0.7 for most models, and calibration was generally poor owing to large between-study heterogeneity, suggesting model overfitting. The clinical utility of the models varied between showing net harm to showing minimal or no net benefit. The average discrimination for IPPIC models ranged between 0.68 and 0.83. This was highest for the second-trimester clinical characteristics and biochemical markers model to predict early-onset pre-eclampsia, and lowest for the first-trimester clinical characteristics models to predict any pre-eclampsia. Calibration performance was heterogeneous across studies. Net benefit was observed for International Prediction of Pregnancy Complications first and second-trimester clinical characteristics and clinical characteristics and biochemical markers models predicting any pre-eclampsia, when validated in singleton nulliparous women managed in the UK NHS. History of hypertension, parity, smoking, mode of conception, placental growth factor and uterine artery pulsatility index had the strongest unadjusted associations with pre-eclampsia. Limitations: Variations in study population characteristics, type of predictors reported, too few events in some validation cohorts and the type of measurements contributed to heterogeneity in performance of the International Prediction of Pregnancy Complications models. Some published models were not validated because model predictors were unavailable in the individual participant data. Conclusion: For models that could be validated, predictive performance was generally poor across data sets. Although the International Prediction of Pregnancy Complications models show good predictive performance on average, and in the singleton nulliparous population, heterogeneity in calibration performance is likely across settings. © 2020, NIHR Journals Library. All rights reserved.

Mechanical stimulation plays in an important role in regulating stem cell differentiation and their release of extracellular vesicles (EVs). In this study, effects of low magnitude hydrostatic pressure (HP) on the chondrogenic differentiation and microvesicle release from human embryonic stem cells (hESCs) and human bone marrow stem cells (hBMSCs) are examined. hESCs were differentiated into chondroprogenitors and then embedded in fibrin gels and subjected to HP (270 kPa, 1 Hz, 5 days per week). hBMSC pellets were differentiated in chondrogenic media and subjected to the same regime. HP significantly enhanced ACAN expression in hESCs. It also led to a significant increase in DNA content, sGAG content and total sGAG/DNA level in hBMSCs. Furthermore, HP significantly increased microvesicle protein content released from both cell types. These results highlight the benefit of HP bioreactor in promoting chondrogenesis and EV production for cartilage tissue engineering.

In this paper, we report the effect of thermal treatment at different temperatures (523, 623, and 723 K) on the magnetic properties of an amorphous powder with composition Fe72.5Si12.5B15 obtained by gas atomization. Differential scanning calorimetry curves indicate that a significant structural rearrangement takes place during annealing before crystallization. As expected, the intrinsic coercivity decreases with the annealing temperature, being the most significant drop from 3.26 to 0.44 Oe for the powder with a particle size $ , non-annealed, and annealed at 723 K, respectively. An analysis of the effect of annealing on the anisotropy field distribution obtained directly from the magnetization curve is presented for both the non-annealed and the annealed sample with the lowest value of coercive field. The probability density function of the anisotropy field exhibits a lower applied field value at the maximum and is better fit by a Gaussian distribution after the heat treatment, which is a sign of better amorphicity after structural relaxation.

Background Myalgic encephalomyelitis (ME) is a complex and debilitating disease that often initially presents with flu-like symptoms, accompanied by incapacitating fatigue. Currently, there are no objective biomarkers or laboratory tests that can be used to unequivocally diagnosis ME; therefore, a diagnosis is made when a patient meets series of a costly and subjective inclusion and exclusion criteria. The purpose of the present study was to evaluate the utility of four clinical parameters in diagnosing ME. Methods In the present study, we utilized logistic regression and classification and regression tree analysis to conduct a retrospective investigation of four clinical laboratory in 140 ME cases and 140 healthy controls. Results Correlations between the covariates ranged between [− 0.26, 0.61]. The best model included the serum levels of the soluble form of CD14 (sCD14), serum levels of prostaglandin E2 (PGE2), and serum levels of interleukin 8, with coefficients 0.002, 0.249, and 0.005, respectively, and p-values of 3 × 10−7, 1 × 10−5, and 3 × 10−3, respectively. Conclusions Our findings show that these parameters may help physicians in their diagnosis of ME and may additionally shed light on the pathophysiology of this disease. Electronic supplementary material The online version of this article (10.1186/s12967-018-1696-z) contains supplementary material, which is available to authorized users.

The gut-brain axis refers to the bidirectional communication between the enteric nervous system and the central nervous system. Mounting evidence supports the premise that the intestinal microbiota plays a pivotal role in its function and has led to the more common and perhaps more accurate term gut-microbiota-brain axis. Numerous studies have identified associations between an altered microbiome and neuroimmune and neuroinflammatory diseases. In most cases, it is unknown if these associations are cause or effect; notwithstanding, maintaining or restoring homeostasis of the microbiota may represent future opportunities when treating or preventing these diseases. In recent years, several studies have identified the diet as a primary contributing factor in shaping the composition of the gut microbiota and, in turn, the mucosal and systemic immune systems. In this review, we will discuss the potential opportunities and challenges with respect to modifying and shaping the microbiota through diet and nutrition in order to treat or prevent neuroimmune and neuroinflammatory disease.

Interesterified fats have largely replaced hydrogenated vegetable fat, which is rich in trans fatty acids, in the food industry as an economically viable alternative, generating interest to study their health effects. The aim of this study was to evaluate the effect that interesterification of oils and fat has on lipid-induced metabolic dysfunction, hepatic inflammation and ER stress. Five week-old male Wistar rats were randomly divided into three experimental groups, submitted to either normocaloric and normolipidic diet containing 10% of lipids from unmodified soybean oil (SO) or from interesterified soybean oil (ISO), and one more group submitted to a high fat diet (HFD) containing 60% of fat from lard as a positive control, for 8 or 16 weeks. Metabolic parameters and hepatic gene expression were evaluated. The HFD consumption led to increased body mass, adiposity and impaired glucose tolerance compared to SO and ISO at both time points of diet. However, the ISO group showed an increased body mass gain, retroperitoneal WAT mass, fasting glucose, and impaired glucose tolerance during ipGTT at 16 weeks compared to SO. Moreover, at 8 weeks, hepatic gene expression of Atf3 and Tnf were increased in the ISO group compared to the SO group. Thus, replacement of natural fat with interesterified fat on a normocaloric and normolipidic diet negatively modulated metabolic parameters and resulted in impaired glucose tolerance in rats.

Working memory training is an emergent field aimed at improving general cognitive abilities through targeted brain exercises. The prospect of improving cognitive abilities, such as attention control, comprehension, and reasoning, has piqued the interest of the scientific community and the general public alike. If cognitive abilities like working memory capacity can be improved, it is assumed that this improvement will result in benefits to a broad range of real-world abilities associated with working memory capacity, including reading comprehension, math performance, and attention control. Thus, the goal of working memory training is to demonstrate broad transfer to tasks that involve the same components of working memory that were targeted during training. Therefore, improvements should be observed on a broad range of tasks that tap the ability being trained. This is measured by observing the difference between pre- and posttest performance on cognitive tasks that subjects have not practiced. The aim of this chapter is to summarize the extant literature on working memory training and then to pose a series of questions to researchers investigating the efficacy of working memory training.

Major depressive disorder (MDD) affects ~20% of the world population and is characterized by strong sexual dimorphism with females being 2–3 times more likely to develop this disorder. Previously, we demonstrated that a combination therapy with dihydrocaffeic acid (DHCA) and malvidin-glucoside (Mal-gluc) to synergistically target peripheral inflammation and stress-induced synaptic maladaptation in the brain was effective in alleviating chronic social defeat stress (CSDS)-induced depression-like phenotype in male mice. Here, we test the combination therapy in a female CSDS model for depression and compared sex-specific responses to stress in the periphery and the central nervous system. Similar to male mice, the combination treatment is also effective in promoting resilience against the CSDS-induced depression-like behavior in female mice. However, there are sex-specific differences in peripheral immune responses and differential gene regulation in the prefrontal cortex to chronic stress and to the treatment. These data indicate that while therapeutic approaches to combat stress-related disorders may be effective in both sexes, the mechanisms underlying these effects differ, emphasizing the need for inclusion of both sexes in preclinical studies using animal models.

Background/Objectives Obesity is an important risk factor for the development of diseases such as diabetes mellitus, hypertension, and dyslipidemia; however, a small number of individuals with long-standing obesity do not present with these cardiometabolic diseases. Such individuals are referred to as metabolically healthy obese (MHO) and potentially represent a subgroup of the general population with a protective genetic predisposition to obesity-related diseases. We hypothesized that individuals who were metabolically healthy but significantly obese (BMI ≥35 kg/m2) would represent a highly homogenous subgroup, with which to investigate potential genetic associations to obesity. We further hypothesized that such a cohort may lend itself well to investigate potential genotypes that are protective with respect to the development of cardiometabolic disease. Subjects/Methods In the present study, we implemented this novel selection strategy by screening 892 individuals diagnosed as Class 2 or Class 3 obese and identified 38 who presented without any manifestations of cardiometabolic disease. We then assessed these subjects for single nucleotide polymorphisms (SNPs) that associated with this phenotype. Results Our analysis identified 89 SNPs that reach statistical significance (p

Autism spectrum disorders (ASD) are severe heterogeneous neurodevelopmental disorders characterized by dysfunctions in social interaction and communication skills, repetitive and stereotypic verbal and nonverbal behaviors. Published findings have identified widespread changes in the immune systems of children with autism, at the systemic and cellular levels, suggesting that autism may, in fact, be a systemic disorder with connections to abnormal immune responses. Evaluating autism is hindered by a lack of specific biomarkers, making these pathologies difficult to diagnose. A critical priority for the future of ASD management is the identification of potential targets for the development of diagnostic and therapeutic strategies. The purpose of this brief report is to raise awareness regarding the involvement of different inflammatory processes in ASD and the need to assess them as a part of a biomedical evaluation. An extensive analysis of biomarkers relating to inflammation, immune dysfunctions, intestinal dysfunctions and infections will assist in the management of the autistic patient through a more personalized therapy.

We report a research describing a new route for the production of Fe-Si-B powders, which is the so-called gas atomisation technology, being one of the challenges to study the conditions under which the glass structure is achieved. There have been produced powders of five different compositions in the Fe-Si-B ternary system. The particles with a diameter below 10 μm of the alloy Fe70Si18B12 (at%) were completely amorphous, exhibiting an excellent soft magnetic behaviour (coercivity of around 7 Oe), which is, without any doubt, of significant scientific merit and supports the use of this new route to produce soft amorphous magnetic materials.

Mystery shopping is a common mode of improving customer service in retail and hospitality businesses, but researchers rarely utilize the methodology in academia. In these business entities, high-le...

The present work is focused on developing amorphisation capability criteria to predict regions with high amorphous forming ability (AFA) in the Fe-Si-B phase diagram. First, the AFA of Fe-Si-B alloy powders was evaluated by conventional empirical glass forming parameters, which eventually did not guide to the best AFA alloy. Then, AFA analysis was extended to the ternary phase diagram, calculated using CALPHAD, along with superimposed mathematical model based on topological instability factor (λ), estimated critical cooling rate (RC) and critical particle size (dC), to confine the phase diagram regions with larger AFA. The alloy with the highest AFA shows optimum atomic size mismatch when λ = 0.204. Furthermore, the optimal region in the phase diagram to design alloys with high AFA is where Fe2B is the first solid phase under equilibrium solidification. Within these two limits, the alloys with lower liquidus temperatures show the highest AFA for the gas-atomised powders.

A thermodynamics-based approach, Calculation of Phase Diagram (CALPHAD), combined with topological instability parameters are proposed and experimentally evaluated, in order to optimise in-situ nanocrystallisation of rapidly quenched CoFeB alloys and exploit their remarkable Bs = 1.57 T. The high Ms of the alloy is attributed to the precipitation of the metastable Co7Fe3 nanocrystalline phase dispersed heterogeneously in the amorphous matrix. High Ms of Co7Fe3 phase can also be inferred from the high hyperfine magnetic field of the Fe nuclei deduced from Mossbauer spectra. It is worth noting that the in-situ nanocrystallisation is a volume phenomenon, instead of surface crystallisation at the air-side of ribbons owning to lower cooling rates. We judge, based on nucleation theory, that the formation of the metastable phase is kinetically favoured, when compared to the equilibrium phases, hence promoting the high Ms, when compared with conventional Co-rich amorphous alloys. The local atomic order of nanocrystallised phase was confirmed by X-ray and electron diffraction techniques. Using Mossbauer spectroscopy and the extracted distribution of the hyperfine magnetic field, it is asserted that cobalt atoms form clusters, as they attract each other to form ordered structures, and boron atoms undergo only short-range ordering, likely due to covalent bond formation, governed by the size and electronegativity differences with the atoms in the amorphous matrix. We suggest the proposed CALPHAD-assisted design of nanostructured alloys, along with an in-situ nanocrystallisation, provides a practical scheme to develop novel functional alloys with the best possible balance of coercivity and saturation, exclusively aimed for a high-tech application.