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Background Animal models used to study pathologies requiring rehabilitation therapy, such as cardiovascular and neurologic disorders or oncologic disease, must be as refined and translationally relevant as possible. Sometimes, however, experimental procedures such as those involving restraint may generate undesired effects which may act as a source of bias. However, the extent to which potentially confounding effects derive from such routine procedures is currently unknown. Our study was therefore aimed at exploring possible undesirable effects of acute restraint stress, whereby animals were exposed to a brightly lit enclosed chamber (R&L) similar to those that are commonly used for substance injection. We hypothesised that this would induce a range of unwanted physiological alterations [such as neuroinflammatory response and changes in body weight and in brown adipose tissue (BAT)] and behavioural modification, and that these might be mitigated via the use of non-aversive handling methods: Tunnel Handling (NAH-T) and Mechanoceptive Handling (NAH-M)) as compared to standard Tail Handling (TH). Methods Two indicators of physiological alterations and three potentially stress sensitive behavioural parameters were assessed. Physiological alterations were recorded via body weight changes and assessing the temperature of Brown Adipose Tissue (BAT) using infra-red thermography (IRT), and at the end of the experiment we determined the concentration of cytokines CXCL12 and CCL2 in bone marrow (BM) and activated microglia in the brain. Nest complexity scoring, automated home-cage behaviour analysis (HCS) and Elevated Plus Maze testing (EPM) were used to detect any behavioural alterations. Recordings were made before and after a 15-minute period of R&L in groups of mice handled via TH, NAH-T or NAH-M. Results BAT temperature significantly decreased in all handling groups following R&L regardless of handling method. There was a difference, at the limit of significance (p = 0.06), in CXCL12 BM content among groups. CXCL12 content in BM of NAH-T animals was similar to that found in Sentinels, the less stressed group of animals. After R&L, mice undergoing NAH-T and NAH-M showed improved body-weight maintenance compared to those exposed to TH. Mice handled via NAH-M spent a significantly longer time on the open arms of the EPM. The HCS results showed that in all mice, regardless of handling method, R&L resulted in a significant reduction in walking and rearing, but not in total distance travelled. All mice also groomed more. No difference among the groups was found in Nest Score, in CCL2 BM content or in brain activated microglia. Conclusions Stress induced by a common restraint procedure caused metabolic and behavioural changes that might increase the risk of unexpected bias. In particular, the significant decrease in BAT temperature could affect the important metabolic pathways controlled by this tissue. R&L lowered the normal frequency of walking and rearing, increased grooming and probably carried a risk of low-grade neuro-inflammation. Some of the observed alterations can be mitigated by Non-aversive handlings.

BackgroundAnimal models used to study pathologies requiring rehabilitation therapy, such as cardiovascular and neurologic disorders or oncologic disease, must be as refined and translationally relevant as possible. Sometimes, however, experimental procedures such as those involving restraint may generate undesired effects which may act as a source of bias. However, the extent to which potentially confounding effects derive from such routine procedures is currently unknown. Our study was therefore aimed at exploring possible undesirable effects of acute restraint stress, whereby animals were exposed to a brightly lit enclosed chamber (R&L) similar to those that are commonly used for substance injection. We hypothesised that this would induce a range of unwanted physiological alterations [such as neuroinflammatory response and changes in body weight and in brown adipose tissue (BAT)] and behavioural modification, and that these might be mitigated via the use of non-aversive handling methods: Tunnel Handling (NAH-T) and Mechanoceptive Handling (NAH-M)) as compared to standard Tail Handling (TH).MethodsTwo indicators of physiological alterations and three potentially stress sensitive behavioural parameters were assessed. Physiological alterations were recorded via body weight changes and assessing the temperature of Brown Adipose Tissue (BAT) using infra-red thermography (IRT), and at the end of the experiment we determined the concentration of cytokines CXCL12 and CCL2 in bone marrow (BM) and activated microglia in the brain. Nest complexity scoring, automated home-cage behaviour analysis (HCS) and Elevated Plus Maze testing (EPM) were used to detect any behavioural alterations. Recordings were made before and after a 15-minute period of R&L in groups of mice handled via TH, NAH-T or NAH-M.ResultsBAT temperature significantly decreased in all handling groups following R&L regardless of handling method. There was a difference, at the limit of significance (p = 0.06), in CXCL12 BM content among groups. CXCL12 content in BM of NAH-T animals was similar to that found in Sentinels, the less stressed group of animals. After R&L, mice undergoing NAH-T and NAH-M showed improved body-weight maintenance compared to those exposed to TH. Mice handled via NAH-M spent a significantly longer time on the open arms of the EPM. The HCS results showed that in all mice, regardless of handling method, R&L resulted in a significant reduction in walking and rearing, but not in total distance travelled. All mice also groomed more. No difference among the groups was found in Nest Score, in CCL2 BM content or in brain activated microglia.ConclusionsStress induced by a common restraint procedure caused metabolic and behavioural changes that might increase the risk of unexpected bias. In particular, the significant decrease in BAT temperature could affect the important metabolic pathways controlled by this tissue. R&L lowered the normal frequency of walking and rearing, increased grooming and probably carried a risk of low-grade neuro-inflammation. Some of the observed alterations can be mitigated by Non-aversive handlings.

Abstract Background Epithelial ovarian cancer (EOC) is a spectrum of different diseases, which makes their treatment a challenge. Forkhead box M1 (FOXM1) is an oncogene aberrantly expressed in many solid cancers including serous EOC, but its role in non-serous EOCs remains undefined. We examined FOXM1 expression and its correlation to prognosis across the three major EOC subtypes, and its role in tumorigenesis and chemo-resistance in vitro. Methods Gene signatures were generated by microarray for 14 clear-cell and 26 endometrioid EOCs, and 15 normal endometrium snap-frozen biopsies. Validation of FOXM1 expression was performed by RT–qPCR and immunohistochemistry in the same samples and additionally in 50 high-grade serous EOCs and in their most adequate normal controls (10 luminal fallopian tube and 20 ovarian surface epithelial brushings). Correlations of FOXM1 expression to clinic-pathological parameters and patients’ prognosis were evaluated by Kaplan-Meier and Cox proportional-hazards analyses. OVCAR-3 and two novel deeply characterized EOC cell lines (EOC-CC1 and OSPC2, with clear-cell and serous subtype, respectively) were employed for in vitro studies. Effects of FOXM1 inhibition by transient siRNA transfection were evaluated on cell-proliferation, cell-cycle, colony formation, invasion, and response to conventional first- and second-line anticancer agents, and to the PARP-inhibitor olaparib. Gene signatures of FOXM1-silenced cell lines were generated by microarray and confirmed by RT-qPCR. Results A significant FOXM1 mRNA up-regulation was found in EOCs compared to normal controls. FOXM1 protein overexpression significantly correlated to serous histology (p = 0.001) and advanced FIGO stage (p = 0.004). Multivariate analyses confirmed FOXM1 protein overexpression as an independent indicator of worse disease specific survival in non-serous EOCs, and of shorter time to progression in platinum-resistant cases. FOXM1 downregulation in EOC cell lines inhibited cell growth and clonogenicity, and promoted the cytotoxic effects of platinum compounds, doxorubicin hydrochloride and olaparib. Upon FOXM1 knock-down in EOC-CC1 and OSPC2 cells, microarray and RT-qPCR analyses revealed the deregulation of several common and other unique subtype-specific FOXM1 putative targets involved in cell cycle, metastasis, DNA repair and drug response. Conclusions FOXM1 is up-regulated in all three major EOCs subtypes, and is a prognostic biomarker and a potential combinatorial therapeutic target in platinum resistant disease, irrespective of tumor histology.

The identification of drugs capable of reactivating γ-globin to ameliorate β-thalassemia and Sickle Cell anemia is still a challenge, as available γ-globin inducers still have limited clinical indications. High-throughput screenings (HTS) aimed to identify new potentially therapeutic drugs require suitable first-step-screening methods combining the possibility to detect variation in the γ/β globin ratio with the robustness of a cell line. We took advantage of a K562 cell line variant expressing β-globin (β-K562) to set up a new multiplexed high-content immunofluorescence assay for the quantification of γ- and β-globin content at single-cell level. The assay was validated by using the known globin inducers hemin, hydroxyurea and butyric acid and further tested in a pilot screening that confirmed HDACs as targets for γ-globin induction (as proved by siRNA-mediated HDAC3 knockdown and by treatment with HDACs inhibitors entinostat and dacinostat) and identified Heme-oxygenases as novel candidate targets for γ-globin induction. Indeed, Heme-oxygenase2 siRNA knockdown as well as its inhibition by Tin protoporphyrin-IX (TinPPIX) greatly increased γ-globin expression. This result is particularly interesting as several metalloporphyrins have already been developed for clinical uses and could be tested (alone or in combination with other drugs) to improve pharmacological γ-globin reactivation for the treatment of β-hemoglobinopathies.

Bike sharing schemes can be used both to improve mobility around busy city routes but also to contribute to the fight against climate change. Optimization of the network in terms of station locations and routes is a focus for researchers, where usage can highlight the precise times at which bike availability is high in some areas and low in others. Locations for new stations are important for the expansion of the network, but spatio-temporal pattern analysis is required to accurately identify those locations. In other words, one cannot rely on spatial information nor temporal information in isolation, when making interpretations for the purpose of optimizing or expanding the network. In this research, a solution based on graph networks was developed to model activity in transport networks by exploiting properties and functions specific to graph databases. This generic approach adopts a broad series of analyses, comprising different levels of granularity and complexity, to enable better interpretation of network dynamics at a suitably granular level to help the optimization of transport networks. A large dataset provided by an electric bike company is used to address key research questions in both interpreting activity patterns and supporting network optimization.

In order for researchers to deliver robust evaluations of time series models, it often requires high volumes of data to ensure the appropriate level of rigor in testing. However, for many researchers, the lack of time series presents a barrier to a deeper evaluation. While researchers have developed and used synthetic datasets, the development of this data requires a methodological approach to testing the entire dataset against a set of metrics which capture the diversity of the dataset. Unless researchers are confident that their test datasets display a broad set of time series characteristics, it may favor one type of predictive model over another. This can have the effect of undermining the evaluation of new predictive methods. In this paper, we present a new approach to generating and evaluating a high number of time series data. The construction algorithm and validation framework are described in detail, together with an analysis of the level of diversity present in the synthetic dataset.