Transcription factor NRF2 protects mice against dietary iron-induced liver injury by preventing hepatocytic cell death

BACKGROUND & AIMS: The liver, being the major site of iron storage, is particularly exposed to the toxic effects of iron. Transcription factor NRF2 is critical for protecting the liver against disease by activating the transcription of genes encoding detoxification/antioxidant enzymes. We aimed to determine if the NRF2 pathway plays a significant role in the protection against hepatic iron overload.METHODS: Wild-type and Nrf2(-/-) mouse primary hepatocytes were incubated with ferric ammonium citrate. Wild-type and Nrf2(-/-) mice were fed standard rodent chow or iron-rich diet for 2weeks, with or without daily injection of the antioxidant mito-TEMPOL.RESULTS: In mouse hepatocytes, iron induced the nuclear translocation of NRF2 and the expression of cytoprotective genes in an NRF2-dependent manner. Moreover, Nrf2(-/-) hepatocytes were highly susceptible to iron-induced cell death. Wild-type and Nrf2(-/-) mice fed iron-rich diet accumulated similar amounts of iron in the liver and were equally able to increase the expression of hepatic hepcidin and ferritin. Nevertheless, in Nrf2-null mice the iron loading resulted in progressive liver injury, ranging from mild confluent necrosis to severe necroinflammatory lesions. Hepatocytic cell death was associated with gross ultrastructural damage to the mitochondria. Notably, liver injury was prevented in iron-fed animals that received mito-TEMPOL.CONCLUSIONS: NRF2 protects the mouse liver against the toxicity of dietary iron overload by preventing hepatocytic cell death. We identify NRF2 as a potential modifier of liver disease in iron overload pathology and show the beneficial effect of the antioxidant mito-TEMPOL in a mouse model of dietary iron-induced liver injury.This work is funded by FEDER Funds through the Operational Competitiveness Programme - COMPETE and by National Funds through FCT - Fundacao para a Ciencia e a Tecnologia under the project FCOMP-01-0124-FEDER-011062 (PTDC/SAU-FCF/101177/2008). TLD is supported by "Programa Ciencia - financiado pelo POPH - QREN - Tipologia 4.2 - Promocao do Emprego Cientifico, comparticipado pelo Fundo Social Europeu e por fundos nacionais do MCTES''

Trochlear Nerve Palsy Associated with Claude Bernard-Horner Syndrome after Brainstem Stroke

The association of unilateral trochlear nerve palsy with Claude Bernard-Horner syndrome represents a rare clinical condition. We present the case of a patient with this unusual presentation. The investigation performed implicated cerebrovascular disease as the underlying cause of the condition in this patient

Abrupt Onset of Second Energy Gap at Superconducting Transition of Underdoped Bi2212

The superconducting gap - an energy scale tied to the superconducting phenomena-opens on the Fermi surface at the superconducting transition temperature (TC) in conventional BCS superconductors. Quite differently, in underdoped high-TC superconducting cuprates, a pseudogap, whose relation to the superconducting gap remains a mystery, develops well above TC. Whether the pseudogap is a distinct phenomenon or the incoherent continuation of the superconducting gap above TC is one of the central questions in high-TC research. While some experimental evidence suggests they are distinct, this issue is still under intense debate. A crucial piece of evidence to firmly establish this two-gap picture is still missing: a direct and unambiguous observation of a single-particle gap tied to the superconducting transition as function of temperature. Here we report the discovery of such an energy gap in underdoped Bi2212 in the momentum space region overlooked in previous measurements. Near the diagonal of Cu-O bond direction (nodal direction), we found a gap which opens at TC and exhibits a canonical (BCS-like) temperature dependence accompanied by the appearance of the so-called Bogoliubov quasiparticles, a classical signature of superconductivity. This is in sharp contrast to the pseudogap near the Cu-O bond direction (antinodal region) measured in earlier experiments. The emerging two-gap phenomenon points to a picture of richer quantum configurations in high temperature superconductors.Comment: 16 pages, 4 figures, authors' version Corrected typos in the abstrac

How to estimate the association between change in a risk factor and a health outcome?

Estimating the effect of a change in a particular risk factor and a chronic disease requires information on the risk factor from two time points; the enrolment and the first follow-up. When using observational data to study the effect of such an exposure (change in risk factor) extra complications arise, namely (i) when is time zero? and (ii) which information on confounders should we account for in this type of analysis? From enrolment or the 1st follow-up? Or from both?. The combination of these questions has proven to be very challenging. Researchers have applied different methodologies with mixed success, because the different choices made when answering these questions induce systematic bias. Here we review these methodologies and highlight the sources of bias in each type of analysis. We discuss the advantages and the limitations of each method ending by making our recommendations on the analysis plan

Disentangling Cooper-pair formation above Tc from the pseudogap state in the cuprates

The discovery of the pseudogap in the cuprates created significant excitement amongst physicists as it was believed to be a signature of pairing, in some cases well above the room temperature. In this "pre-formed pairs" scenario, the formation of pairs without quantum phase rigidity occurs below T*. These pairs condense and develop phase coherence only below Tc. In contrast, several recent experiments reported that the pseudogap and superconducting states are characterized by two different energy scales, pointing to a scenario, where the two compete. However a number of transport, magnetic, thermodynamic and tunneling spectroscopy experiments consistently detect a signature of phase-fluctuating superconductivity above leaving open the question of whether the pseudogap is caused by pair formation or not. Here we report the discovery of a spectroscopic signature of pair formation and demonstrate that in a region of the phase diagram commonly referred to as the "pseudogap", two distinct states coexist: one that persists to an intermediate temperature Tpair and a second that extends up to T*. The first state is characterized by a doping independent scaling behavior and is due to pairing above Tc, but significantly below T*. The second state is the "proper" pseudogap - characterized by a "checker board" pattern in STM images, the absence of pair formation, and is likely linked to Mott physics of pristine CuO2 planes. Tpair has a universal value around 130-150K even for materials with very different Tc, likely setting limit on highest, attainable Tc in cuprates. The observed universal scaling behavior with respect to Tpair indicates a breakdown of the classical picture of phase fluctuations in the cuprates.Comment: 9 pages, 4 figure

On the estimation of the effect of weight change on a health outcome using observational data, by utlilising the target trial emulation framework

Background/Objectives: When studying the effect of weight change between two time points on a health outcome using observational data, two main problems arise initially (i) ‘when is time zero?’ and (ii) ‘which confounders should we account for?’ From the baseline date or the 1st follow-up (when the weight change can be measured)? Different methods have been previously used in the literature that carry different sources of bias and hence produce different results. Methods: We utilised the target trial emulation framework and considered weight change as a hypothetical intervention. First, we used a simplified example from a hypothetical randomised trial where no modelling is required. Then we simulated data from an observational study where modelling is needed. We demonstrate the problems of each of these methods and suggest a strategy. Interventions: weight loss/gain vs maintenance. Results: The recommended method defines time-zero at enrolment, but adjustment for confounders (or exclusion of individuals based on levels of confounders) should be performed both at enrolment and the 1st follow-up. Conclusions: The implementation of our suggested method [adjusting for (or excluding based on) confounders measured both at baseline and the 1st follow-up] can help researchers attenuate bias by avoiding some common pitfalls. Other methods that have been widely used in the past to estimate the effect of weight change on a health outcome are more biased. However, two issues remain (i) the exposure is not well-defined as there are different ways of changing weight (however we tried to reduce this problem by excluding individuals who develop a chronic disease); and (ii) immortal time bias, which may be small if the time to first follow up is short

Symptoms and quality of life in late stage Parkinson syndromes: a longitudinal community study of predictive factors

BACKGROUND Palliative care is increasingly offered earlier in the cancer trajectory but rarely in Idiopathic Parkinson's Disease(IPD), Progressive Supranuclear Palsy(PSP) or Multiple System Atrophy(MSA). There is little longitudinal data of people with late stage disease to understand levels of need. We aimed to determine how symptoms and quality of life of these patients change over time; and what demographic and clinical factors predicted changes. METHODS We recruited 82 patients into a longitudinal study, consenting patients with a diagnosis of IPD, MSA or PSP, stages 3-5 Hoehn and Yahr(H&Y). At baseline and then on up to 3 occasions over one year, we collected self-reported demographic, clinical, symptom, palliative and quality of life data, using Parkinson's specific and generic validated scales, including the Palliative care Outcome Scale (POS). We tested for predictors using multivariable analysis, adjusting for confounders. FINDINGS Over two thirds of patients had severe disability, over one third being wheelchair-bound/bedridden. Symptoms were highly prevalent in all conditions - mean (SD) of 10.6(4.0) symptoms. More than 50% of the MSA and PSP patients died over the year. Over the year, half of the patients showed either an upward (worsening, 24/60) or fluctuant (8/60) trajectory for POS and symptoms. The strongest predictors of higher levels of symptoms at the end of follow-up were initial scores on POS (AOR 1.30; 95%CI:1.05-1.60) and being male (AOR 5.18; 95% CI 1.17 to 22.92), both were more predictive than initial H&Y scores. INTERPRETATION The findings point to profound and complex mix of non-motor and motor symptoms in patients with late stage IPD, MSA and PSP. Symptoms are not resolved and half of the patients deteriorate. Palliative problems are predictive of future symptoms, suggesting that an early palliative assessment might help screen for those in need of earlier intervention

Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting

Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post—the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases with over 1 million deaths. The high infection rates coupled with dynamic population movement demands for tools, especially within a Brazilian context, that will support health managers to develop policies for controlling and combating the new virus. / Methods: In this work, we propose a tool for real-time spatio-temporal analysis using a machine learning approach. The COVID-SGIS system brings together routinely collected health data on Covid-19 distributed across public health systems in Brazil, as well as taking to under consideration the geographic and time-dependent features of Covid-19 so as to make spatio-temporal predictions. The data are sub-divided by federative unit and municipality. In our case study, we made spatio-temporal predictions of the distribution of cases and deaths in Brazil and in each federative unit. Four regression methods were investigated: linear regression, support vector machines (polynomial kernels and RBF), multilayer perceptrons, and random forests. We use the percentage RMSE and the correlation coefficient as quality metrics. / Results: For qualitative evaluation, we made spatio-temporal predictions for the period from 25 to 27 May 2020. Considering qualitatively and quantitatively the case of the State of Pernambuco and Brazil as a whole, linear regression presented the best prediction results (thematic maps with good data distribution, correlation coefficient >0.99 and RMSE (%) <4% for Pernambuco and around 5% for Brazil) with low training time: [0.00; 0.04 ms], CI 95%. / Conclusion: Spatio-temporal analysis provided a broader assessment of those in the regions where the accumulated confirmed cases of Covid-19 were concentrated. It was possible to differentiate in the thematic maps the regions with the highest concentration of cases from the regions with low concentration and regions in the transition range. This approach is fundamental to support health managers and epidemiologists to elaborate policies and plans to control the Covid-19 pandemics