A Metachronous splenic metastases from esophageal cancer: a case report

The spleen is an infrequent site for metastatic lesions, and solitary splenic metastases from squamous cell carcinoma of the esophagus are very rare: only 4 cases have been reported thus far. These lesions are whitish nodules that are macroscopically and radiologically similar to primary splenic lymphomas. We report a case of metachronous splenic metastases from esophageal cancer and multiple splenic abscesses, which developed nine months after apparently curative esophagectomy without adjuvant chemotherapy. The patient underwent splenectomy dissection followed by adjuvant chemotherapy, but liver and skin metastases developed, and the patient died 9 months later

A Spoonful of Math Helps the Medicine Go Down: An Illustration of How Healthcare can Benefit from Mathematical Modeling and Analysis

<p>Abstract</p> <p>Objectives</p> <p>A recent joint report from the Institute of Medicine and the National Academy of Engineering, highlights the benefits of--indeed, the need for--mathematical analysis of healthcare delivery. Tools for such analysis have been developed over decades by researchers in Operations Research (OR). An OR perspective typically frames a complex problem in terms of its essential mathematical structure. This article illustrates the use and value of the tools of operations research in healthcare. It reviews one OR tool, queueing theory, and provides an illustration involving a hypothetical drug treatment facility.</p> <p>Method</p> <p>Queueing Theory (QT) is the study of waiting lines. The theory is useful in that it provides solutions to problems of waiting and its relationship to key characteristics of healthcare systems. More generally, it illustrates the strengths of modeling in healthcare and service delivery.</p> <p>Queueing theory offers insights that initially may be hidden. For example, a queueing model allows one to incorporate randomness, which is inherent in the actual system, into the mathematical analysis. As a result of this randomness, these systems often perform much worse than one might have guessed based on deterministic conditions. Poor performance is reflected in longer lines, longer waits, and lower levels of server utilization.</p> <p>As an illustration, we specify a queueing model of a representative drug treatment facility. The analysis of this model provides mathematical expressions for some of the key performance measures, such as average waiting time for admission.</p> <p>Results</p> <p>We calculate average occupancy in the facility and its relationship to system characteristics. For example, when the facility has 28 beds, the average wait for admission is 4 days. We also explore the relationship between arrival rate at the facility, the capacity of the facility, and waiting times.</p> <p>Conclusions</p> <p>One key aspect of the healthcare system is its complexity, and policy makers want to design and reform the system in a way that affects competing goals. OR methodologies, particularly queueing theory, can be very useful in gaining deeper understanding of this complexity and exploring the potential effects of proposed changes on the system without making any actual changes.</p

Synergistic binding of transcription factors to cell-specific enhancers programs motor neuron identity

Efficient transcriptional programming promises to open new frontiers in regenerative medicine. However, mechanisms by which programming factors transform cell fate are unknown, preventing more rational selection of factors to generate desirable cell types. Three transcription factors, Ngn2, Isl1 and Lhx3, were sufficient to program rapidly and efficiently spinal motor neuron identity when expressed in differentiating mouse embryonic stem cells. Replacement of Lhx3 by Phox2a led to specification of cranial, rather than spinal, motor neurons. Chromatin immunoprecipitation–sequencing analysis of Isl1, Lhx3 and Phox2a binding sites revealed that the two cell fates were programmed by the recruitment of Isl1-Lhx3 and Isl1-Phox2a complexes to distinct genomic locations characterized by a unique grammar of homeodomain binding motifs. Our findings suggest that synergistic interactions among transcription factors determine the specificity of their recruitment to cell type–specific binding sites and illustrate how a single transcription factor can be repurposed to program different cell types.Project ALS FoundationNational Institutes of Health (U.S.) (Grant P01 NS055923

Major histocompatibility complex class I molecules protect motor neurons from astrocyte-induced toxicity in amyotrophic lateral sclerosis

Astrocytes isolated from individuals with amyotrophic lateral sclerosis (ALS) are toxic to motor neurons (MNs) and play a non–cell autonomous role in disease pathogenesis. The mechanisms underlying the susceptibility of MNs to cell death remain unclear. Here we report that astrocytes derived from either mice bearing mutations in genes associated with ALS or human subjects with ALS reduce the expression of major histocompatibility complex class I (MHCI) molecules on MNs; reduced MHCI expression makes these MNs susceptible to astrocyte-induced cell death. Increasing MHCI expression on MNs increases survival and motor performance in a mouse model of ALS and protects MNs against astrocyte toxicity. Overexpression of a single MHCI molecule, HLA-F, protects human MNs from ALS astrocyte–mediated toxicity, whereas knockdown of its receptor, the killer cell immunoglobulin-like receptor KIR3DL2, on human astrocytes results in enhanced MN death. Thus, our data indicate that, in ALS, loss of MHCI expression on MNs renders them more vulnerable to astrocyte-mediated toxicity

Comparing individual-based approaches to modelling the self-organization of multicellular tissues.

The coordinated behaviour of populations of cells plays a central role in tissue growth and renewal. Cells react to their microenvironment by modulating processes such as movement, growth and proliferation, and signalling. Alongside experimental studies, computational models offer a useful means by which to investigate these processes. To this end a variety of cell-based modelling approaches have been developed, ranging from lattice-based cellular automata to lattice-free models that treat cells as point-like particles or extended shapes. However, it remains unclear how these approaches compare when applied to the same biological problem, and what differences in behaviour are due to different model assumptions and abstractions. Here, we exploit the availability of an implementation of five popular cell-based modelling approaches within a consistent computational framework, Chaste (http://www.cs.ox.ac.uk/chaste). This framework allows one to easily change constitutive assumptions within these models. In each case we provide full details of all technical aspects of our model implementations. We compare model implementations using four case studies, chosen to reflect the key cellular processes of proliferation, adhesion, and short- and long-range signalling. These case studies demonstrate the applicability of each model and provide a guide for model usage

Problems of multi-species organisms: endosymbionts to holobionts

The organism is one of the fundamental concepts of biology and has been at the center of many discussions about biological individuality, yet what exactly it is can be confusing. The definition that we find generally useful is that an organism is a unit in which all the subunits have evolved to be highly cooperative, with very little conflict. We focus on how often organisms evolve from two or more formerly independent organisms. Two canonical transitions of this type—replicators clustered in cells and endosymbiotic organelles within host cells—demonstrate the reality of this kind of evolutionary transition and suggest conditions that can favor it. These conditions include co-transmission of the partners across generations and rules that strongly regulate and limit conflict, such as a fair meiosis. Recently, much attention has been given to associations of animals with microbes involved in their nutrition. These range from tight endosymbiotic associations like those between aphids and Buchnera bacteria, to the complex communities in animal intestines. Here, starting with a reflection about identity through time (which we call “Theseus’s fish”), we consider the distinctions between these kinds of animal–bacteria interactions and describe the criteria by which a few can be considered jointly organismal but most cannot

The labels and models used to describe problematic substance use impact discrete elements of stigma: A registered report.

Objectives: Problematic substance use is one of the most stigmatized health conditions leading research to examine how the labels and models used to describe it influence public stigma. Two recent studies examine whether beliefs in a disease model of addiction influence public stigma but result in equivocal findings—in line with the mixed-blessings model, Kelly et al. (2021) found that while the label “chronically relapsing brain disease” reduced blame attribution, it decreased prognostic optimism and increased perceived danger and need for continued care; however, Rundle et al. (2021) conclude absence of evidence. This study isolates the different factors used in these two studies to assess whether health condition (drug use vs. health concern), etiological label (brain disease vs. problem), and attributional judgment (low vs. high treatment stability) influence public stigma toward problematic substance use. Method: Overall, 1,613 participants were assigned randomly to one of the eight vignette conditions that manipulated these factors. They completed self-report measures of discrete and general public stigma and an indirect measure of discrimination. Results: Greater social distance, danger, and public stigma but lower blame were ascribed to drug use relative to a health concern. Greater (genetic) blame was reported when drug use was labelled as a “chronically relapsing brain disease” relative to a “problem.” Findings for attributional judgment were either inconclusive or statistically equivalent. Discussion: The labels used to describe problematic substance use appear to impact discrete elements of stigma. We suggest that addiction is a functional attribution, which may explain the mixed literature on the impact of etiological labels on stigma to date

International money markets: eurocurrencies

Eurocurrencies are international markets for short-term wholesale bank deposits and loans. They emerged in Western Europe in the late 1950s and rapidly reached a global scale. A Eurocurrency is a form of bank money: an unsecured short-term bank debt denominated in a currency (for instance, US dollars) but issued by banks operating offshore, in a geographical location or a legal space situated outside of the jurisdiction of the national authorities presiding over that currency (for instance, the Federal Reserve). In Eurocurrency markets, banks intermediate mainly between foreign residents. They borrow funds by "accepting" foreign currency deposits and lend foreign currency-denominated funds by "placing" deposits with other banks, by granting short-term loans or investing in other liquid assets. Historically, Eurodollars accounted for the largest share of Eurocurrencies, although other international currencies (Deutsche Marks, Japanese yens, and especially Euros since 1999) played an important role. Eurocurrency markets were a manifestation of financial integration and interdependence in a globalizing economy and performed critical functions in the distribution and creation of international liquidity. At the same time, their fast growth was a recurrent source of concerns for central bankers and policymakers due to their implications for macroeconomic policies and financial stability. This chapter analyzes different aspects of the historical development of Eurocurrency markets and their role in the international monetary and financial system. The first part discusses theoretical interpretations, presents estimates of markets' size, describes their structure, and explains the determinants of their growth. The second part analyzes the spread between Eurodollar rates and other US money market rates, the role of arbitrage, the evolution of risk factors, and the causes of historical episodes of stress and contagion in the interbank market. The last part discusses political economy issues, such as the role of governments and market forces in the emergence of Eurodollars in the 1950s and the failed attempts to impose multilateral controls on Eurocurrency markets in the 1970s