Trends in Use of Lymphadenectomy in Surgery with Curative Intent for Intrahepatic Cholangiocarcinoma

Background: The role of routine lymph node dissection (LND) in the surgical treatment of intrahepatic cholangiocarcinoma (ICC) remains controversial. The objective of this study was to investigate the trends of LND use in the surgical treatment of ICC. Methods: Patients undergoing curative intent resection for ICC in 2000-2015 were identified from an international multi-institutional database. Use of lymphadenectomy was evaluated over time and by geographical region (West versus East); LND use and final nodal status were analysed relative to AJCC T categories. Results: Among the 1084 patients identified, half (535, 49·4 per cent) underwent concomitant hepatic resection and LND. Between 2000 and 2015, the proportion of patients undergoing LND for ICC nearly doubled: 44·4 per cent in 2000 versus 81·5 per cent in 2015 (P < 0·001). Use of LND increased over time among both Eastern and Western centres. The odds of LND was associated with the time period of surgery and the extent of the tumour/T status (referent T1a: OR 2·43 for T2, P = 0·001; OR 2·13 for T3, P = 0·016). Among the 535 patients who had LND, lymph node metastasis (LNM) was noted in 209 (39·1 per cent). Specifically, the incidence of LNM was 24 per cent in T1a disease, 22 per cent in T1b, 42·9 per cent in T2, 48 per cent in T3 and 66 per cent in T4 (P < 0·001). AJCC T3 and T4 categories, harvesting of six or more lymph nodes, and presence of satellite lesions were independently associated with LNM. Conclusion: The rate of LNM was high across all T categories, with one in five patients with T1 disease having nodal metastasis. The trend in increased use of LND suggests a growing adoption of AJCC recommendations in the treatment of ICC.info:eu-repo/semantics/publishedVersio

Madagascar corals track sea surface temperature variability in the Agulhas Current core region over the past 334 years

The Agulhas Current (AC) is the strongest western boundary current in the Southern Hemisphere and is key for weather and climate patterns, both regionally and globally. Its heat transfer into both the midlatitude South Indian Ocean and South Atlantic is of global significance. A new composite coral record (Ifaty and Tulear massive Porites corals), is linked to historical AC sea surface temperature (SST) instrumental data, showing robust correlations. The composite coral SST data start in 1660 and comprise 200 years more than the AC instrumental record. Numerical modelling exhibits that this new coral derived SST record is representative for the wider core region of the AC. AC SSTs variabilities show distinct cooling through the Little Ice Age and warming during the late 18th, 19th and 20th century, with significant decadal variability superimposed. Furthermore, the AC SSTs are teleconnected with the broad southern Indian and Atlantic Oceans, showing that the AC system is pivotal for inter-ocean heat exchange south of Africa

MicroRNA-Related Cofilin Abnormality in Alzheimer's Disease

Rod-like structures composed of actin and the actin-binding protein cofilin are found in Alzheimer's disease (AD) patients. However, the mechanisms underlying formation of these structures and their pathological consequences are still largely unknown. We found that microRNAs 103 and 107 repress translation of cofilin, and that reduced levels of miR-103 or miR-107 are associated with elevated cofilin protein levels and formation of rod-like structures in a transgenic mouse model of AD. These results suggest that microRNAs may play an important role in cytoskeletal pathology in AD

Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling

<p>Abstract</p> <p>Background</p> <p>With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few approaches have studied subtle and indirect interaction such as genetic compensation, the existence of which is widely recognized although its mechanism has yet to be clarified. Furthermore, when inferring gene networks most models include only observed variables whereas latent factors, such as proteins and mRNA degradation that are not measured by microarrays, do participate in networks in reality.</p> <p>Results</p> <p>Motivated by inferring transcriptional compensation (TC) interactions in yeast, a stepwise structural equation modeling algorithm (SSEM) is developed. In addition to observed variables, SSEM also incorporates hidden variables to capture interactions (or regulations) from latent factors. Simulated gene networks are used to determine with which of six possible model selection criteria (MSC) SSEM works best. SSEM with Bayesian information criterion (BIC) results in the highest true positive rates, the largest percentage of correctly predicted interactions from all existing interactions, and the highest true negative (non-existing interactions) rates. Next, we apply SSEM using real microarray data to infer TC interactions among (1) small groups of genes that are synthetic sick or lethal (SSL) to SGS1, and (2) a group of SSL pairs of 51 yeast genes involved in DNA synthesis and repair that are of interest. For (1), SSEM with BIC is shown to outperform three Bayesian network algorithms and a multivariate autoregressive model, checked against the results of qRT-PCR experiments. The predictions for (2) are shown to coincide with several known pathways of Sgs1 and its partners that are involved in DNA replication, recombination and repair. In addition, experimentally testable interactions of Rad27 are predicted.</p> <p>Conclusion</p> <p>SSEM is a useful tool for inferring genetic networks, and the results reinforce the possibility of predicting pathways of protein complexes via genetic interactions.</p

Comparative Composition, Diversity and Trophic Ecology of Sediment Macrofauna at Vents, Seeps and Organic Falls

Sediments associated with hydrothermal venting, methane seepage and large organic falls such as whale, wood and plant detritus create deep-sea networks of soft-sediment habitats fueled, at least in part, by the oxidation of reduced chemicals. Biological studies at deep-sea vents, seeps and organic falls have looked at macrofaunal taxa, but there has yet to be a systematic comparison of the community-level attributes of sediment macrobenthos in various reducing ecosystems. Here we review key similarities and differences in the sediment-dwelling assemblages of each system with the goals of (1) generating a predictive framework for the exploration and study of newly identified reducing habitats, and (2) identifying taxa and communities that overlap across ecosystems. We show that deep-sea seep, vent and organic-fall sediments are highly heterogeneous. They sustain different geochemical and microbial processes that are reflected in a complex mosaic of habitats inhabited by a mixture of specialist (heterotrophic and symbiont-associated) and background fauna. Community-level comparisons reveal that vent, seep and organic-fall macrofauna are very distinct in terms of composition at the family level, although they share many dominant taxa among these highly sulphidic habitats. Stress gradients are good predictors of macrofaunal diversity at some sites, but habitat heterogeneity and facilitation often modify community structure. The biogeochemical differences across ecosystems and within habitats result in wide differences in organic utilization (i.e., food sources) and in the prevalence of chemosynthesis-derived nutrition. In the Pacific, vents, seeps and organic-falls exhibit distinct macrofaunal assemblages at broad-scales contributing to ß diversity. This has important implications for the conservation of reducing ecosystems, which face growing threats from human activities

Dopamine Inhibits Mitochondrial Motility in Hippocampal Neurons

The trafficking of mitochondria within neurons is a highly regulated process. In an earlier study, we found that serotonin (5-HT), acting through the 5-HT1A receptor subtype, promotes axonal transport of mitochondria in cultured hippocampal neurons by increasing Akt activity, and consequently decreasing glycogen synthase kinase (GSK3beta) activity. This finding suggests a critical role for neuromodulators in the regulation of mitochondrial trafficking in neurons. In the present study, we investigate the effects of a second important neuromodulator, dopamine, on mitochondrial transport in hippocampal neurons.Here, we show that dopamine, like 5-HT, regulates mitochondrial motility in cultured hippocampal neurons through the Akt-GSK3beta signaling cascade. But, in contrast to the stimulatory effect of 5-HT, administration of exogenous dopamine or bromocriptine, a dopamine 2 receptor (D2R) agonist, caused an inhibition of mitochondrial movement. Moreover, pretreatment with bromocriptine blocked the stimulatory effect of 5-HT on mitochondrial movement. Conversely, in cells pretreated with 5-HT, no further increases in movement were observed after administration of haloperidol, a D2R antagonist. In contrast to the effect of the D2R agonist, addition of SKF38393, a dopamine 1 receptor (D1R) agonist, promoted mitochondrial transport, indicating that the inhibitory effect of dopamine was actually the net summation of opposing influences of the two receptor subtypes. The most pronounced effect of dopamine signals was on mitochondria that were already moving directionally. Western blot analysis revealed that treatment with either a D2R agonist or a D1R antagonist decreased Akt activity, and conversely, treatment with either a D2R antagonist or a D1R agonist increased Akt activity.Our observations strongly suggest a role for both dopamine and 5-HT in regulating mitochondrial movement, and indicate that the integrated effects of these two neuromodulators may be important in determining the distribution of energy sources in neurons

Active Inference, Novelty and Neglect

In this chapter, we provide an overview of the principles of active inference. We illustrate how different forms of short-term memory are expressed formally (mathematically) through appealing to beliefs about the causes of our sensations and about the actions we pursue. This is used to motivate an approach to active vision that depends upon inferences about the causes of 'what I have seen' and learning about 'what I would see if I were to look there'. The former could manifest as persistent 'delay-period' activity - of the sort associated with working memory, while the latter is better suited to changes in synaptic efficacy - of the sort that underlies short-term learning and adaptation. We review formulations of these ideas in terms of active inference, their role in directing visual exploration and the consequences - for active vision - of their failures. To illustrate the latter, we draw upon some of our recent work on the computational anatomy of visual neglect

iTRAQ Analysis of Complex Proteome Alterations in 3xTgAD Alzheimer's Mice: Understanding the Interface between Physiology and Disease

Alzheimer's disease (AD) is characterized by progressive cognitive impairment associated with accumulation of amyloid β-peptide, synaptic degeneration and the death of neurons in the hippocampus, and temporal, parietal and frontal lobes of the cerebral cortex. Analysis of postmortem brain tissue from AD patients can provide information on molecular alterations present at the end of the disease process, but cannot discriminate between changes that are specifically involved in AD versus those that are simply a consequence of neuronal degeneration. Animal models of AD provide the opportunity to elucidate the molecular changes that occur in brain cells as the disease process is initiated and progresses. To this end, we used the 3xTgAD mouse model of AD to gain insight into the complex alterations in proteins that occur in the hippocampus and cortex in AD. The 3xTgAD mice express mutant presenilin-1, amyloid precursor protein and tau, and exhibit AD-like amyloid and tau pathology in the hippocampus and cortex, and associated cognitive impairment. Using the iTRAQ stable-isotope-based quantitative proteomic technique, we performed an in-depth proteomic analysis of hippocampal and cortical tissue from 16 month old 3xTgAD and non-transgenic control mice. We found that the most important groups of significantly altered proteins included those involved in synaptic plasticity, neurite outgrowth and microtubule dynamics. Our findings have elucidated some of the complex proteome changes that occur in a mouse model of AD, which could potentially illuminate novel therapeutic avenues for the treatment of AD and other neurodegenerative disorders