Umbrella review and network meta-analysis of diagnostic imaging test accuracy studies in Differentiating between brain tumor progression versus pseudoprogression and radionecrosis

PURPOSE

In this study we gathered and analyzed the available evidence regarding 17 different imaging modalities and performed network meta-analysis to find the most effective modality for the differentiation between brain tumor recurrence and post-treatment radiation effects.

METHODS

We conducted a comprehensive systematic search on PubMed and Embase. The quality of eligible studies was assessed using the Assessment of Multiple Systematic Reviews-2 (AMSTAR-2) instrument. For each meta-analysis, we recalculated the effect size, sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio from the individual study data provided in the original meta-analysis using a random-effects model. Imaging technique comparisons were then assessed using NMA. Ranking was assessed using the multidimensional scaling approach and by visually assessing surface under the cumulative ranking curves.

RESULTS

We identified 32 eligible studies. High confidence in the results was found in only one of them, with a substantial heterogeneity and small study effect in 21% and 9% of included meta-analysis respectively. Comparisons between MRS Cho/NAA, Cho/Cr, DWI, and DSC were most studied. Our analysis showed MRS (Cho/NAA) and 18F-DOPA PET displayed the highest sensitivity and negative likelihood ratios. 18-FET PET was ranked highest among the 17 studied techniques with statistical significance. APT MRI was the only non-nuclear imaging modality to rank higher than DSC, with statistical insignificance, however.

CONCLUSION

The evidence regarding which imaging modality is best for the differentiation between radiation necrosis and post-treatment radiation effects is still inconclusive. Using NMA, our analysis ranked FET PET to be the best for such a task based on the available evidence. APT MRI showed promising results as a non-nuclear alternative.

Cilostazol pretreatment prevents PTSD-related anxiety behavior through reduction of hippocampal neuroinflammation

Current pharmacological treatments against post-traumatic stress disorder (PTSD) lack adequate efficacy. As a result, intense research has focused on identifying other molecular pathways mediating the pathogenesis of this condition. One such pathway is neuroinflammation, which has demonstrated a role in PTSD pathogenesis by causing synaptic dysfunction, neuronal death, and functional impairment in the hippocampus. Phosphodiesterase (PDE) inhibitors (PDEIs) have emerged as promising therapeutic agents against neuroinflammation in other neurological conditions. Furthermore, PDEIs have shown some promise in animal models of PTSD. However, the current model of PTSD pathogenesis, which is based on dysregulated fear learning, implies that PDE inhibition in neurons should enhance the acquisition of fear memory from the traumatic event. As a result, we hypothesized that PDEIs may improve PTSD symptoms through inhibiting neuroinflammation rather than long-term potentiation-related mechanisms. To this end, we tested the therapeutic efficacy of cilostazol, a selective inhibitor of PDE3, on PTSD-related anxiety symptoms in the underwater trauma model of PTSD. PDE3 is expressed much more richly in microglia and astrocytes compared to neurons in the murine brain. Furthermore, we used hippocampal indolamine 2,3-dioxygenase 1 (IDO) expression and interleukin 1 beta (IL-1β) concentration as indicators of neuroinflammation. We observed that cilostazol pretreatment prevented the development of anxiety symptoms and the increase in hippocampal IDO and IL-1β following PTSD induction. As a result, PDE3 inhibition ameliorated the neuroinflammatory processes involved in the development of PTSD symptoms. Therefore, cilostazol and other PDEIs may be promising candidates for further investigation as pharmacological therapies against PTSD.

Prevalence and Features of Post-stroke Urinary Incontinence: A Retrospective Cohort Study

BACKGROUND

Long-term complications of stroke, persisting for more than 6 months after the initial event, substantially reduce the quality of life (QoL) in a significant percentage of stroke survivors. In this paper, we studied the prevalence of long-term urinary incontinence (UI) in post-stroke patients. In addition, we attempted to identify patient characteristics which were associated with higher UI prevalence, higher UI severity, and less UI-associated QoL.

METHODS

Medical records in a tertiary referral hospital were used to contact patients who had experienced a stroke between 6 to 32 months before the study date. The patients were given the International Consultation on Incontinence Questionnaire Short Form (ICIQ-UI-SF) questionnaire for determining the presence of UI and its severity. UI-positive patients were then given the I-QOL questionnaire to determine their QoL.

RESULTS

The prevalence of UI in our study population (n=189) was 31%. Older age at the time of stroke was associated with higher UI severity (r=0.290) and lower QoL (r=-0.265). Furthermore, the presence of movement limitation was associated with higher UI prevalence (P<0.001, OR=3.89) and severity (P=0.002, d=1.05). Movement limitation also significantly impacted the psychological and social aspects of UI-associated QoL (P=0.035, d=-0.74). Conversely, higher body mass indices (BMIs) were associated with lower UI severity (r=-0.346) and higher QoL (r=0.281).

CONCLUSION

In conclusion, UI continues to be prevalent in stroke survivors long after the cerebrovascular accident (CVA). As a result, these patients require continuous monitoring and UI prevention.

Phosphodiesterase inhibitors in psychiatric disorders

RATIONALE

Challenges in drug development for psychiatric disorders have left much room for the introduction of novel treatments with better therapeutic efficacies and indices. As a result, intense research has focused on identifying new targets for developing such pharmacotherapies. One of these targets may be the phosphodiesterase (PDE) class of enzymes, which play important roles in intracellular signaling. Due to their critical roles in cellular pathways, these enzymes affect diverse neurobiological functions from learning and memory formation to neuroinflammation.

OBJECTIVES

In this paper, we reviewed studies on the use of PDE inhibitors (PDEIs) in preclinical models and clinical trials of psychiatric disorders including depression, anxiety, schizophrenia, post-traumatic stress disorder (PTSD), bipolar disorder (BP), sexual dysfunction, and feeding disorders.

RESULTS

PDEIs are able to improve symptoms of psychiatric disorders in preclinical models through activating the cAMP-PKA-CREB and cGMP-PKG pathways, attenuating neuroinflammation and oxidative stress, and stimulating neural plasticity. The most promising therapeutic candidates to emerge from these preclinical studies are PDE2 and PDE4 inhibitors for depression and anxiety and PDE1 and PDE10 inhibitors for schizophrenia. Furthermore, PDE3 and 4 inhibitors have shown promising results in clinical trials in patients with depression and schizophrenia.

CONCLUSIONS

Larger and better designed clinical studies of PDEIs in schizophrenia, depression, and anxiety are warranted to facilitate their translation into the clinic. Regarding the other conditions discussed in this review (most notably PTSD and BP), better characterization of the effects of PDEIs in preclinical models is required before clinical studies.

OutSingle: A Novel Method of Detecting and Injecting Outliers in RNA-seq Count Data Using the Optimal Hard Threshold for Singular Values

MOTIVATION

Finding outliers in RNA Sequencing (RNA-Seq) gene expression (GE) can help in identifying genes that are aberrant and cause Mendelian disorders. Recently developed models for this task rely on modeling RNA-Seq GE data using the Negative Binomial distribution (NBD). However, some of those models either rely on procedures for inferring NBD's parameters in a non-biased way that are computationally demanding, and thus make confounder control challenging, while others rely on less computationally demanding but biased procedures and convoluted confounder control approaches that hinder interpretability.

RESULTS

In this paper we present OutSingle (Outlier detection using Singular Value Decomposition), an almost instantaneous way of detecting outliers in RNA-Seq GE data. It uses a simple log-normal approach for count modeling. For confounder control it uses the recently discovered Optimal Hard Threshold (OHT) method for noise detection, which itself is based on Singular Value Decomposition (SVD). Due to its SVD/OHT utilization, OutSingle's model is straightforward to understand and interpret. We then show that our novel method, when used on RNA-Seq GE data with real biological outliers masked by confounders, outcompetes the previous state-of-the art model based on an ad-hoc denoising autoencoder (AE). Additionally, OutSingle can be used to inject artificial outliers masked by confounders, which is difficult to achieve with previous approaches. We describe a way of using OutSingle for outlier injection and proceed to show how OutSingle outperforms its competition on 16 out of 18 datasets that were generated from 3 real datasets using OutSingle's injection procedure with different outlier types and magnitudes. Our methods are applicable to other types of similar problems involving finding outliers in matrices under the presence of confounders.

AVAILABILITY

The code for OutSingle is available at https://github.com/esalkovic/outsingle.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Spermidine reduced neuropathic pain in chronic constriction injury-induced peripheral neuropathy in rats

Neuropathic pain is one of the most critical types of chronic pain despite the increasing advances in medical science. Spermidine (SPD) is a natural polyamine that has wide roles in several cellular processes inducing autophagy and reducing oxidative stress. This study aimed to investigate the effects of SPD on oxidative stress markers and pain threshold in the neuropathic rat model of chronic constriction injury (CCI) model. Eighteen adult male rats were divided into three groups: sham, CCI and CCI+SPD. After induction of neuropathy via CCI model in the CCI and CCI+SPD groups, SPD (1 mg/kg/day, orally) was administered to the CCI+SPD group for 3 weeks. The behavioral tests (von Frey, hot plate) were done four times during the experiment. At the end of the study, electrophysiological tests, the H & E staining, and oxidative stress assay of the prefrontal cortex (PFC), spinal cord, and sciatic nerve were performed. The threshold of pain in hot plate and von Frey tests was significantly lower in the CCI group than in the sham group, which was reversed by SPD treatment in the CCI+ SPD group. In addition, nerve conduction was considerably lower in the CCI group than in the sham and CCI+SPD groups (P < 0.01, P < 0.05, respectively). The CCI group showed neuronal degeneration and fibrosis in the different tissues in the H & E assay; elevated tissues level of nitrite, decreased levels of superoxide dismutase (SOD), glutathione (GPx), and catalase were also observed. However, SPD treatment modulated the pathological changes and oxidative stress biomarkers. In conclusion, SPD showed beneficial effects in decreasing neuropathic pains. SPD treatment reduced oxidative stress and improved histopathological changes and behavioral tests in the CCI-induced neuropathic pain in in vivo model.

Targeting neuronal nitric oxide synthase and the nitrergic system in post-traumatic stress disorder

RATIONALE

Current pharmacological approaches to treatment of post-traumatic stress disorder (PTSD) lack adequate effectiveness. As a result, identifying new molecular targets for drug development is necessary. Furthermore, fear learning and memory in PTSD can undergo different phases, such as fear acquisition, consolidation, and extinction. Each phase may involve different cellular pathways and brain regions. As a result, effective management of PTSD requires mindfulness of the timing of drug administration. One of the molecular targets currently under intense investigation is the N-methyl-D-aspartate (NMDA)-type glutamate receptor (NMDAR). However, despite the therapeutic efficacy of drugs targeting NMDAR, their translation into clinical use has been challenging due to their various side effects. One possible solution to this problem is to target signaling proteins downstream to NMDAR to improve targeting specificity. One of these proteins is the neuronal nitric oxide synthase (nNOS), which is activated following calcium influx through the NMDAR.

OBJECTIVE

In this paper, we review the literature on the pharmacological modulation of nNOS in animal models of PTSD to evaluate its therapeutic potential. Furthermore, we attempt to decipher the inconsistencies observed between the findings of these studies based on the specific phase of fear learning which they had targeted.

RESULTS

Inhibition of nNOS may inhibit fear acquisition and recall, while not having a significant effect on fear consolidation and extinction. However, it may improve extinction consolidation or reconsolidation blockade.

CONCLUSIONS

Modulation of nNOS has therapeutic potential against PTSD and warrants further development for use in the clinical setting.

Association between Promotor hypomethylation of TFF1 and Crohn's Disease

BACKGROUND AND AIM

Epigenetic modifications exhibit promising evidence in etiology and prognosis of important diseases such as inflammatory bowel diseases (IBD). In addition to complex factors involved in IBD, a trend toward better prognosis have been reported in older ages of disease onset. Gastrointestinal mucous layer is one of the important components which is disturbed in the disease course. Integrity of this layer is maintained with an anti-inflammatory factor called trefoil factors (TFF). We investigated the methylation status of TFF1 gene in IBD patients alongside with correlation of its alteration level with age of disease onset.

METHODS

We analyzed the promoter methylation status of TFF1 gene, using the real-time quantitative multiplex methylation specific PCR (QM-MSP). DNA was extracted from colorectal biopsies of 15 Crohn disease cases and 15 healthy controls. Correlation analysis was performed between unmethylated DNA level and age through Pearson correlation coefficient (PPC) test and simple linear regression models.

RESULTS

… Our data didn't provide significant positive correlation of age and TFF1 hypomethylation in Crohn patients (r = .518, p = .058).

CONCLUSIONS

In conclusion, our case-control study didn't show significant alteration in TFF1 methylation status in CD patients. (www.actabiomedica.it).

Challenges of cancer immunotherapy and chemotherapy during the COVID-19 pandemic

People at high risk of morbidity and mortality from coronavirus disease 2019 (COVID-19), including patients dealing with malignancies and patients on immunosuppressive anticancer therapies, need to be followed carefully as the pandemic continues. Challenges in continuing cancer management and patient monitoring are of concern given the importance of timing in cancer therapy. Alternative treatment decisions and priorities are also important considerations. The efficacy and safety of various cancer treatments in patients with COVID-19 are other important considerations. In this systematic review, we summarize the potential risks and benefits of cancer treatments applied to patients with COVID-19 and malignant tumors. Using the PubMed and Scopus databases, we reviewed studies involving cancer therapy and COVID-19 to address the recent discoveries and related challenges of cancer therapy in patients with COVID-19 and cancer.

Evaluation of Anti-inflammatory and Antioxidant Effects of Sumatriptan on Carbon Tetrachloride-induced Hepatotoxicity in Rats

The liver detoxifies and metabolizes many drugs and xenobiotics which may cause hepatotoxicity due to some toxic agents. Carbon tetrachloride (CCl₄) is metabolized in cytochrome P450 and its reactive radical metabolites cause lipid peroxidation, cellular injury, and apoptosis. Sumatriptan (SUM), 5-HT1B/1D receptor agonist, had anti-inflammatory and anti-oxidant effects. In this research the effect of SUM pre-treatment against CCl₄-induced hepatotoxicity was examined. Adult rats received SUM (0.1, 0.3 and 1 mg/kg; i.p.) for 3 consecutive days before CCl₄ (2 ml/kg; i.p. on the 3^rd day). The aminotransferases serum levels, tissue levels of anti-oxidant and pro-inflammatory markers and histopathological examination were evaluated. SUM (0.3 mg/kg) prevented significantly the elevation of aminotransferases versus the control group (CCl₄ group) (P<0.0001) and also, reversed meaningfully the changes of the MPO, MDA, SOD and CAT, IL-1β and TNF-α levels. Additionally, CCl₄-intoxication resulted to the disruption of lobular and cellular structures and inflammation in histopathological evaluation which is prevented by SUM (0.3 mg/kg). These data revealed that SUM (0.3 mg/kg), but no at doses 0.1 and 1 mg/kg, decreases the hepatotoxicity of induced by CCl₄ in rats.

Chronically altered NMDAR signaling in epilepsy mediates comorbid depression

Depression is the most common psychiatric comorbidity of epilepsy. However, the molecular pathways underlying this association remain unclear. The NMDA receptor (NMDAR) may play a role in this association, as its downstream signaling has been shown to undergo long-term changes following excitotoxic neuronal damage. To study this pathway, we used an animal model of fluoxetine-resistant epilepsy-associated depression (EAD). We determined the molecular changes associated with the development of depressive symptoms and examined their response to various combinations of fluoxetine and a selective neuronal nitric oxide synthase inhibitor, 7-nitroindazole (NI). Depressive symptoms were determined using the forced swim test. Furthermore, expression and phosphorylation levels of markers in the ERK/CREB/ELK1/BDNF/cFOS pathway were measured to determine the molecular changes associated with these symptoms. Finally, oxidative stress markers were measured to more clearly determine the individual contributions of each treatment. While chronic fluoxetine (Flxc) and NI were ineffective alone, their combination had a statistically significant synergistic effect in reducing depressive symptoms. The development of depressive symptoms in epileptic rats was associated with the downregulation of ERK2 expression and ELK1 and CREB phosphorylation. These changes were exactly reversed upon Flxc + NI treatment, which led to increased BDNF and cFOS expression as well. Interestingly, ERK1 did not seem to play a role in these experiments. NI seemed to have augmented Flxc’s antidepressant activity by reducing oxidative stress. Our findings suggest NMDAR signaling alterations are a major contributor to EAD development and a potential target for treating conditions associated with underlying excitotoxic neuronal damage.

High-Performance Estimation of Lead Ion Concentration Using Smartphone-Based Colorimetric Analysis and a Machine Learning Approach

Traditional methods for detection of lead ions in water samples are costly and time-consuming. In this work, an accurate smartphone-based colorimetric sensor was developed utilizing a novel machine learning algorithm. In the presence of Pb²⁺ ions in the solution of specifically functionalized gold nanoparticles, the color of solution turns from red to purple. Indeed, the color variation of the solution is proportional to Pb²⁺ concentration. The smartphone camera captures the corresponding color change, and the image is processed by an efficient artificial intelligence protocol. The nonlinear regression approach was used for concentration estimation, in which the parameters of the proposed model are obtained using a new feature extraction algorithm. In prediction of Pb²⁺ concentration, the average absolute error and root-mean-square error were 0.094 and 0.124, respectively. The influence of pH of the medium, temperature, oligonucleotide concentration, and reaction time on the performance of the proposed sensor was carefully investigated and understood to achieve the best sensor response. This novel sensor exhibited good linearity for the detection of Pb²⁺ in the concentration range of 0.5-2000 ppb with a detection limit of 0.5 ppb.

Protective Effects of Leukadherin1 in a Rat Model of Targeted Experimental Autoimmune Encephalomyelitis (EAE): Possible Role of P47phox and MDA Downregulation

Background

Reactive oxygen and nitrogen species (ROS and RNS) are involved in pathologic mechanisms underlying demyelination and exacerbation in multiple sclerosis (MS) lesions. P47phox is the most important subunit of an ROS-producing enzyme (NADPH oxidase) which is reportedly upregulated in MS plaques due to the intense activity of infiltrated immune cells and resident microglia. Leukadherin1 is a specific CD11b/CD18 agonist that inhibits signaling and transmigration of inflammatory cells to sites of injury. Based on this mechanism, we evaluated therapeutic effects of leukadherin1 in an animal model of targeted experimental autoimmune encephalomyelitis (EAE) through focal injection of inflammatory cytokines to the spinal cord.

Methods

For model induction, Lewis rats were first immunized with 15µg MOG 1–125 emulsion. Twenty days later, animals were subjected to stereotaxic injection of IFNγ and TNFα to the specific spinal area (T8). One day after injection, all animals presented EAE clinical signs, and their behaviors were monitored for eight days through open-field locomotion and grid-walking tests. Leukadherin1-treated animals received daily intraperitoneal injections of 1mg/kg of the drug. The specific spinal tissues were extracted on day 5 in order to measure nitric oxide (NO), malon di-aldehyde (MDA), and TNFα concentrations alongside P47phox real-time PCR analysis. In addition, spinal sections were prepared for immunohistochemical (IHC) observation of infiltrated leukocytes and activated microglia.

Results

Leukadherin1 exhibited promising improvements in EAE clinical scores and behavioral tests. Demyelination, CD45+ leukocyte infiltration, and Iba1+ microglia activation were reduced in spinal tissues of leukadherin1-treated animals. Furthermore, P47phox expression levels, MDA, and NO amounts were decreased in treated animals. However, TNFα concentrations did not differ following treatment.

Conclusion

Based on our results, we suggest that leukadherin1 may be used as a novel therapeutic agent in tackling the clinical challenge of multiple sclerosis, especially during the acute phase of the disease. This effect was possibly mediated through decreased leukocyte infiltration and oxidative stress.

Hepatoprotective Effects of Standardized Extracts from an Ancient Italian Apple Variety (Mela Rosa dei Monti Sibillini) against Carbon Tetrachloride (CCl4)-Induced Hepatotoxicity in Rats

The aim of this research was to examine the effect of the hydroalcoholic extracts from the peel (APE) and pulp (APP) of a traditional apple cultivar from central Italy (Mela Rosa dei Monti Sibillini) on CCl4-induced hepatotoxicity in rats. Phytoconstituents were determined by liquid chromatography-mass spectrometry (LC-MS) analysis showing an abundance of proanthocyanidins and flavonol derivatives together with the presence of annurcoic acid in APE. Wistar rats received APE/APP (30 mg/kg oral administration) for three days before CCl4 injection (2 mL/kg intraperitoneal once on the third day). Treatment with both APE and APP prior to CCl4 injection significantly decreased the serum levels of aspartate aminotransferase (AST), alkaline phosphatase (ALP) and alanine aminotransferase (ALT) compared to the CCl4 group. Besides, pretreatment with APE reversed the CCl4 effects on superoxide dismutase (SOD), myeloperoxidase (MPO), tumor necrosis factor-α (TNF-α) and interleukin-1beta (IL-1β) levels in liver tissue in rats and reduced tissue damage as shown in hematoxylin and eosin staining. These results showed that this ancient Italian apple is worthy of use in nutraceuticals and dietary supplements to prevent and/or protect against liver disorders.

Dye Removal Using Hairy Nanocellulose: Experimental and Theoretical Investigations

Adsorption is a common technique for the treatment of dye-contaminated wastewater. Achieving a high dye removal capacity is a common challenge with sustainable, low-cost adsorbents. Recently, a class of easily functionalized, biorenewable cellulose nanoparticles called hairy nanocellulose has been developed. Electrosterically stabilized nanocrystalline cellulose (ENCC), which can be synthesized from wood pulp through a two-step oxidation by periodate and chlorite, is a form of hairy nanocellulose with a high negative charge density, and thus has the potential for a high adsorption capacity. In this work, the adsorption of methylene blue, a cationic dye, by ENCC was shown to occur up to charge stoichiometry (1400 mg dye/g adsorbent), at which point aggregation of ENCC-dye complexes is observed. A model is developed to show that the adsorption can be described by an ion-exchange mechanism and is influenced by the presence of other ions. Equilibrium dye removal is reduced at both high ionic strengths and low pH. To facilitate handling, composite hydrogel beads of sodium alginate and ENCC (ALG-ENCC beads) are developed, and their methylene blue removal capacity is shown to maintain a high removal capacity (1250 mg/g). ALG-ENCC beads provide a facile way to employ these nanoparticles on a larger scale, providing a potential means for the removal of dyes and other contaminants at larger wastewater volumes.

Dispersion modeling in pore networks: A comparison of common pore-scale models and alternative approaches

Mass transfer in porous media resulting from dispersion occurs in a wide variety of applications such as water treatment, flow batteries, flow in aquifers, enhanced oil recovery, and packed-bed reactors. The underlying mechanisms of dispersion are the molecular diffusion superimposed on the advective transport induced by the fluid flow. Modeling dispersion in pore networks can be performed at a much lower computational cost compared to that in direct numerical simulations (DNS) such as finite element or the lattice Boltzmann methods, so it can be regarded as a suitable alternative provided its accuracy is sufficient. The most common approach to model dispersion in network models is based on the first-order upwind scheme, despite its known limitations in terms of accuracy for certain flow and transport regimes. In this study, three alternative pore-scale models for dispersion, which are more accurate than the existing ones, were derived and tested in pore network simulations. These models were adopted from the CFD literature and are based on a spatial discretization of the advection-diffusion equation using the hybrid and power-law finite difference schemes and the exact solution of the one-dimensional advection-diffusion equation. Finally, considering dispersion problems over arbitrary porous structures, consisting of stick-and-ball geometries, and different flow and mass transfer arrangements, the developed models were validated. Validation was carried-out through comparisons between results obtained with DNS, using a finite element solver, and those from pore network simulations. It is shown that under a wide range of dispersion regimes (up to the onset of the dispersion power-law regime), the relative error (with respect to DNS results) introduced by the power-law and exact solution-based models is consistently below 1%, whereas the use of the upwind scheme leads to >10% of relative error, depending on the dispersion regime. All the dispersion models developed in this study were implemented as part of the open-source network modeling package, OpenPNM.

The antidepressant effects of GM-CSF are mediated by the reduction of TLR4/NF-ĸB-induced IDO expression

BACKGROUND

Indoleamine 2, 3-dioxygenase 1 (IDO) is responsible for the progression of the kynurenine pathway. This pathway has been implicated in the pathophysiology of inflammation-induced depression in which conventional antidepressants are not effective. It has been reported that granulocyte-macrophage stimulating factor (GM-CSF) could interfere with the induction of IDO in septic patients. We hypothesized that GM-CSF could exert antidepressant effects through IDO downregulation in a model for acute inflammation-induced depression.

METHODS

To produce the model, lipopolysaccharide (LPS) (0.83 mg/kg) was administered intraperitoneally to mice. It has been well documented that LPS mediates IDO overexpression through TLR4/NF-ĸB signaling. In the treatment group, mice received GM-CSF (30 μg/kg, i.p.) thirty minutes prior to LPS injection. A validated selective serotonin reuptake inhibitor, fluoxetine (30 mg/kg i.p.), was also administered to an experimental group 30 min prior to LPS. Depressive-like behaviors were evaluated based on the duration of immobility in the forced swim test. To confirm that GM-CSF interferes with IDO induction in LPS treated mice, real-time PCR was used to quantify IDO mRNA expression. Furthermore, in order to study whether GM-CSF inhibits the TLR4/NF-ĸB signaling pathway, we measured levels ofpNF-ĸB and TLR4 by western blotting.

RESULTS

GM-CSF demonstrated significant antidepressant activity in the presence of LPS on immobility (p < .001) and latency (p = .010) times in the forced swim test. In contrast, fluoxetine did not show any antidepressant activity on either immobility (p = .918) or latency (p = .566) times. Furthermore, GM-CSF inhibited the increase in IDO mRNA (p = .032) and protein (p = .016) expression as a result of LPS administration. A similar trend was observed for TLR4 (p = .042) and pNF-ĸB (p = .026) expression as both proteins showed reduced expression levels in the GM-CSF-pretreated group compared to the untreated (LPS) group.

CONCLUSION

Our results propose a promising antidepressant effect for GM-CSF possibly through the downregulation of IDO expression. This remedying effect of GM-CSF could be attributed to decreased amounts of TLR4 and active NF-ĸB in the treated mice.

Phrasal recognition

In this paper, we introduce visual phrases, complex visual composites like "a person riding a horse." Visual phrases often display significantly reduced visual complexity compared to their component objects because the appearance of those objects can change profoundly when they participate in relations. We introduce a dataset suitable for phrasal recognition that uses familiar PASCAL object categories, and demonstrate significant experimental gains resulting from exploiting visual phrases. We show that a visual phrase detector significantly outperforms a baseline which detects component objects and reasons about relations, even though visual phrase training sets tend to be smaller than those for objects. We argue that any multiclass detection system must decode detector outputs to produce final results; this is usually done with nonmaximum suppression. We describe a novel decoding procedure that can account accurately for local context without solving difficult inference problems. We show this decoding procedure outperforms the state of the art. Finally, we show that decoding a combination of phrasal and object detectors produces real improvements in detector results.