USE-Net: Incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets

Prostate cancer is the most common malignant tumors in men but prostate Magnetic Resonance Imaging (MRI) analysis remains challenging. Besides whole prostate gland segmentation, the capability to differentiate between the blurry boundary of the Central Gland (CG) and Peripheral Zone (PZ) can lead to differential diagnosis, since tumor's frequency and severity differ in these regions. To tackle the prostate zonal segmentation task, we propose a novel Convolutional Neural Network (CNN), called USE-Net, which incorporates Squeeze-and-Excitation (SE) blocks into U-Net. Especially, the SE blocks are added after every Encoder (Enc USE-Net) or Encoder-Decoder block (Enc-Dec USE-Net). This study evaluates the generalization ability of CNN-based architectures on three T2-weighted MRI datasets, each one consisting of a different number of patients and heterogeneous image characteristics, collected by different institutions. The following mixed scheme is used for training/testing: (i) training on either each individual dataset or multiple prostate MRI datasets and (ii) testing on all three datasets with all possible training/testing combinations. USE-Net is compared against three state-of-the-art CNN-based architectures (i.e., U-Net, pix2pix, and Mixed-Scale Dense Network), along with a semi-automatic continuous max-flow model. The results show that training on the union of the datasets generally outperforms training on each dataset separately, allowing for both intra-/cross-dataset generalization. Enc USE-Net shows good overall generalization under any training condition, while Enc-Dec USE-Net remarkably outperforms the other methods when trained on all datasets. These findings reveal that the SE blocks' adaptive feature recalibration provides excellent cross-dataset generalization when testing is performed on samples of the datasets used during training.Comment: 44 pages, 6 figures, Accepted to Neurocomputing, Co-first authors: Leonardo Rundo and Changhee Ha

Global parameter search reveals design principles of the mammalian circadian clock

Background: Virtually all living organisms have evolved a circadian (~24 hour) clock that controls physiological and behavioural processes with exquisite precision throughout the day/night cycle. The suprachiasmatic nucleus (SCN), which generates these ~24 h rhythms in mammals, consists of several thousand neurons. Each neuron contains a gene-regulatory network generating molecular oscillations, and the individual neuron oscillations are synchronised by intercellular coupling, presumably via neurotransmitters. Although this basic mechanism is currently accepted and has been recapitulated in mathematical models, several fundamental questions about the design principles of the SCN remain little understood. For example, a remarkable property of the SCN is that the phase of the SCN rhythm resets rapidly after a 'jet lag' type experiment, i.e. when the light/ dark (LD) cycle is abruptly advanced or delayed by several hours. Results: Here, we describe an extensive parameter optimization of a previously constructed simplified model of the SCN in order to further understand its design principles. By examining the top 50 solutions from the parameter optimization, we show that the neurotransmitters' role in generating the molecular circadian rhythms is extremely important. In addition, we show that when a neurotransmitter drives the rhythm of a system of coupled damped oscillators, it exhibits very robust synchronization and is much more easily entrained to light/dark cycles. We were also able to recreate in our simulations the fast rhythm resetting seen after a 'jet lag' type experiment. Conclusion: Our work shows that a careful exploration of parameter space for even an extremely simplified model of the mammalian clock can reveal unexpected behaviours and non-trivial predictions. Our results suggest that the neurotransmitter feedback loop plays a crucial role in the robustness and phase resetting properties of the mammalian clock, even at the single neuron level

A Phosphoproteomic Approach towards the Understanding of the Role of TGF-β in Trypanosoma cruzi Biology

Transforming growth factor beta (TGF-β) plays a pivotal role in Chagas disease, not only in the development of chagasic cardiomyopathy, but also in many stages of the T. cruzi life cycle and survival in the host cell environment. The intracellular signaling pathways utilized by T. cruzi to regulate these mechanisms remain unknown. To identify parasite proteins involved in the TGF-β response, we utilized a combined approach of two-dimensional gel electrophoresis (2DE) analysis and mass spectrometry (MS) protein identification. Signaling via TGF-β is dependent on events of phosphorylation, which is one of the most relevant and ubiquitous post-translational modifications for the regulation of gene expression, and especially in trypanosomatids, since they lack several transcriptional control mechanisms. Here we show a kinetic view of T. cruzi epimastigotes (Y strain) incubated with TGF-β for 1, 5, 30 and 60 minutes, which promoted a remodeling of the parasite phosphorylation network and protein expression pattern. The altered molecules are involved in a variety of cellular processes, such as proteolysis, metabolism, heat shock response, cytoskeleton arrangement, oxidative stress regulation, translation and signal transduction. A total of 75 protein spots were up- or down-regulated more than twofold after TGF-β treatment, and from these, 42 were identified by mass spectrometry, including cruzipain–the major T. cruzi papain-like cysteine proteinase that plays an important role in invasion and participates in the escape mechanisms used by the parasite to evade the host immune system. In our study, we observed that TGF-β addition favored epimastigote proliferation, corroborating 2DE data in which proteins previously described to be involved in this process were positively stimulated by TGF-β

Influence of the oxygen microenvironment on the proangiogenic potential of human endothelial colony forming cells

Therapeutic angiogenesis is a promising strategy to promote the formation of new or collateral vessels for tissue regeneration and repair. Since changes in tissue oxygen concentrations are known to stimulate numerous cell functions, these studies have focused on the oxygen microenvironment and its role on the angiogenic potential of endothelial cells. We analyzed the proangiogenic potential of human endothelial colony-forming cells (hECFCs), a highly proliferative population of circulating endothelial progenitor cells, and compared outcomes to human dermal microvascular cells (HMVECs) under oxygen tensions ranging from 1% to 21% O2, representative of ischemic or healthy tissues and standard culture conditions. Compared to HMVECs, hECFCs (1) exhibited significantly greater proliferation in both ischemic conditions and ambient air; (2) demonstrated increased migration compared to HMVECs when exposed to chemotactic gradients in reduced oxygen; and (3) exhibited comparable or superior proangiogenic potential in reduced oxygen conditions when assessed using a vessel-forming assay. These data demonstrate that the angiogenic potential of both endothelial populations is influenced by the local oxygen microenvironment. However, hECFCs exhibit a robust angiogenic potential in oxygen conditions representative of physiologic, ischemic, or ambient air conditions, and these findings suggest that hECFCs may be a superior cell source for use in cell-based approaches for the neovascularization of ischemic or engineered tissues

Bioelectrical impedance phase angle in clinical practice: implications for prognosis in stage IIIB and IV non-small cell lung cancer

<p>Abstract</p> <p>Background</p> <p>A frequent manifestation of advanced lung cancer is malnutrition, timely identification and treatment of which can lead to improved patient outcomes. Bioelectrical impedance analysis (BIA) is an easy-to-use and non-invasive technique to evaluate changes in body composition and nutritional status. We investigated the prognostic role of BIA-derived phase angle in advanced non-small cell lung cancer (NSCLC).</p> <p>Methods</p> <p>A case series of 165 stages IIIB and IV NSCLC patients treated at our center. The Kaplan Meier method was used to calculate survival. Cox proportional hazard models were constructed to evaluate the prognostic effect of phase angle, independent of stage at diagnosis and prior treatment history.</p> <p>Results</p> <p>93 were males and 72 females. 61 had stage IIIB disease at diagnosis while 104 had stage IV. The median phase angle was 5.3 degrees (range = 2.9 – 8). Patients with phase angle <= 5.3 had a median survival of 7.6 months (95% CI: 4.7 to 9.5; n = 81), while those with > 5.3 had 12.4 months (95% CI: 10.5 to 18.7; n = 84); (p = 0.02). After adjusting for age, stage at diagnosis and prior treatment history we found that every one degree increase in phase angle was associated with a relative risk of 0.79 (95% CI: 0.64 to 0.97, P = 0.02).</p> <p>Conclusion</p> <p>We found BIA-derived phase angle to be an independent prognostic indicator in patients with stage IIIB and IV NSCLC. Nutritional interventions targeted at improving phase angle could potentially lead to an improved survival in patients with advanced NSCLC.</p

Bioelectrical impedance phase angle as a prognostic indicator in breast cancer

<p>Abstract</p> <p>Background</p> <p>Bioelectrical impedance analysis (BIA) is an easy-to-use, non-invasive, and reproducible technique to evaluate changes in body composition and nutritional status. Phase angle, determined by bioelectrical impedance analysis (BIA), detects changes in tissue electrical properties and has been hypothesized to be a marker of malnutrition. Since malnutrition can be found in patients with breast cancer, we investigated the prognostic role of phase angle in breast cancer.</p> <p>Methods</p> <p>We evaluated a case series of 259 histologically confirmed breast cancer patients treated at Cancer Treatment Centers of America. Kaplan Meier method was used to calculate survival. Cox proportional hazard models were constructed to evaluate the prognostic effect of phase angle independent of stage at diagnosis and prior treatment history. Survival was calculated as the time interval between the date of first patient visit to the hospital and the date of death from any cause or date of last contact/last known to be alive.</p> <p>Results</p> <p>Of 259 patients, 81 were newly diagnosed at our hospital while 178 had received prior treatment elsewhere. 56 had stage I disease at diagnosis, 110 had stage II, 46 had stage III and 34 had stage IV. The median age at diagnosis was 49 years (range 25 – 74 years). The median phase angle score was 5.6 (range = 1.5 – 8.9). Patients with phase angle <= 5.6 had a median survival of 23.1 months (95% CI: 14.2 to 31.9; n = 129), while those > 5.6 had 49.9 months (95% CI: 35.6 to 77.8; n = 130); the difference being statistically significant (p = 0.031). Multivariate Cox modeling, after adjusting for stage at diagnosis and prior treatment history found that every one unit increase in phase angle score was associated with a relative risk of 0.82 (95% CI: 0.68 to 0.99, P = 0.041). Stage at diagnosis (p = 0.006) and prior treatment history (p = 0.001) were also predictive of survival independent of each other and phase angle.</p> <p>Conclusion</p> <p>This study demonstrates that BIA-derived phase angle is an independent prognostic indicator in patients with breast cancer. Nutritional interventions targeted at improving phase angle could potentially lead to an improved survival in patients with breast cancer.</p

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo

We use data from the second science run of the LIGO gravitational-wave detectors to search for the gravitational waves from primordial black hole (PBH) binary coalescence with component masses in the range 0.2--$1.0 M_\odot$. The analysis requires a signal to be found in the data from both LIGO observatories, according to a set of coincidence criteria. No inspiral signals were found. Assuming a spherical halo with core radius 5 kpc extending to 50 kpc containing non-spinning black holes with masses in the range 0.2--$1.0 M_\odot$, we place an observational upper limit on the rate of PBH coalescence of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.