Uplifting manhood to wonderful heights? News coverage of the human costs of military conflict from world war I to Gulf war Two

Domestic political support is an important factor constraining the use of American military power around the world. Although the dynamics of war support are thought to reflect a cost-benefit calculus, with costs represented by numbers of friendly war deaths, no previous study has examined how information about friendly, enemy, and civilian casualties is routinely presented to domestic audiences. This paper establishes a baseline measure of historical casualty reporting by examining New York Times coverage of five major wars that occurred over the past century. Despite important between-war differences in the scale of casualties, the use of conscription, the type of warfare, and the use of censorship, the frequency of casualty reporting and the framing of casualty reports has remained fairly consistent over the past 100 years. Casualties are rarely mentioned in American war coverage. When casualties are reported, it is often in ways that minimize or downplay the human costs of war

Wars, Presidents and Popularity: The Political Cost(s) of War Re-Examined

Extensive research demonstrates that war casualties depress incumbent popularity. The present study argues that analyses of the political costs of warfare should also account for the financial toll of wars since a) financial costs of wars are substantial, b) these costs are publicly observed and understood and c) fiscal policy affects incumbents' approval ratings. Empirical evidence based on US data for the 1948-2008 period supports this theoretical claim: pecuniary costs of warfare either directly affect presidential popularity (e.g., in the Korean War) or their inclusion affects the predicted political cost of war casualties (e.g., in the Korean and Iraq/Afghanistan Wars). Interestingly, the adverse effect of war-spending is strongest under favourable economic conditions (i.e. low unemployment).Umfangreiche Forschungen zeigen, dass Kriegsopfer der Popularität des Amtsinhabers schaden. Die vorliegende Studie liefert Argumente dafür, dass Analysen der politischen Kosten der Kriegsführung in die Berechnung der finanziellen Kriegsausgaben miteinbezogen werden sollten, da a) die finanziellen Kosten von Kriegen beträchtlich sind, b) diese Kosten von der Öffentlichkeit wahrgenommen und verstanden werden, c) Fiskalpolitik die Umfragewerte des Amtsinhabers beeinflusst. Basierend auf US-Daten über den Zeitraum 1948-2008 wird dieser theoretische Anspruch empirisch unterstützt: pekuniäre Kosten der Kriegsführung haben entweder direkt eine Auswirkung auf die Popularität des Präsidenten (z. B. Koreakrieg) oder deren Einbeziehung beeinflusst die vorhergesagten politischen Kosten durch Kriegsopfer (z. B. Korea- und Irak/-Afghanistankrieg). Interessanterweise sind die negativen Auswirkungen der Kriegsausgaben am stärksten, wenn die wirtschaftlichen Bedingungen günstig (d.h. niedrige Arbeitslosigkeit) sind

Fatal Rocky Mountain Spotted Fever along the United States–Mexico Border, 2013–2016

Rocky Mountain spotted fever (RMSF) is an emerging public health concern near the US–Mexico border, where it has resulted in thousands of cases and hundreds of deaths in the past decade. We identified 4 patients who had acquired RMSF in northern Mexico and subsequently died at US healthcare facilities. Two patients sought care in Mexico before being admitted to US-based hospitals. All patients initially had several nonspecific signs and symptoms, including fever, headache, nausea, vomiting, or myalgia, but deteriorated rapidly without receipt of a tetracycline-class antimicrobial drug. Each patient experienced respiratory failure late in illness. Although transborder cases are not common, early recognition and prompt initiation of appropriate treatment are vital for averting severe illness and death. Clinicians on both sides of the US–Mexico border should consider a diagnosis of RMSF for patients with rapidly progressing febrile illness and recent exposure in northern Mexico

High-Plex Spatial RNA Profiling Reveals Cell Type‒Specific Biomarker Expression during Melanoma Development.

Early diagnosis of melanoma is critical for improved survival. However, the biomarkers of early melanoma evolution and their origin within the tumor and its microenvironment, including the keratinocytes, are poorly defined. To address this, we used spatial transcript profiling that maintains the morphological tumor context to measure the expression of >1,000 RNAs in situ in patient-derived formalin-fixed, paraffin-embedded tissue sections in primary melanoma and melanocytic nevi. We profiled 134 regions of interest (each 200 μm in diameter) enriched in melanocytes, neighboring keratinocytes, or immune cells. This approach captured distinct expression patterns across cell types and tumor types during melanoma development. Unexpectedly, we discovered that S100A8 is expressed by keratinocytes within the tumor microenvironment during melanoma growth. Immunohistochemistry of 252 tumors showed prominent keratinocyte-derived S100A8 expression in melanoma but not in benign tumors and confirmed the same pattern for S100A8's binding partner S100A9, suggesting that injury to the epidermis may be an early and readily detectable indicator of melanoma development. Together, our results establish a framework for high-plex, spatial, and cell type‒specific resolution of gene expression in archival tissue applicable to the development of biomarkers and characterization of tumor microenvironment interactions in tumor evolution

Laparoscopic Cholecystectomy - a Standardized Routine Laparoscopic Procedure: Is it Possible to Predict the Duration of an Operation?

In order to improve operating room efficiency, it is desirable to predict the duration of scheduled surgeries as precisely as possible. The reliability of existing predicting models is less than satisfactory. This study presents an algorithm to estimate the operating time for laparoscopic cholecystectomy, based on historical data of 312 patients, taking into account clinical parameters, diagnostic imaging, and surgeon's experience. The algorithm's accuracy was evaluated in a group of 45 patients by prospectively predicting their operating times. It was shown that increased information significantly reduced prediction error. The prediction error of our algorithm was estimated to be 17.5 minutes (95%CI: 16.5 to 18.8 minutes), whereas that of the univariable random effect model (using solely surgeon's experience as the explanation factor) was 21.6 minutes (95%CI: 20.3 to 23.1 minutes)