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The Plague of Ashdod (1630) Nicholas Poussin
The artwork “The Plague of Ashdod” was created by the French painter Nicolas Poussin in 1630. It portrays the biblical narrative of a divine plague inflicted upon the people of Ashdod.
This dramatic scene of divine punishment is described in the Old Testament. The Philistines are stricken with plague in their city of Ashdod because they have stolen the Ark of the Covenant from the Israelites and placed it in their pagan temple. You can see the decorated golden casket of the Ark between the pillars of the temple. People look around in horror at their dead and dying companions. One man leans over the corpses of his wife and child and covers his nose to avoid the stench. Rats scurry towards the bodies. The broken statue of their deity, Dagon, and the tumbled down stone column further convey the Philistines’ downfall.
In the artwork, Poussin vividly depicts the turmoil and suffering caused by the plague. The foreground is filled with the stricken inhabitants of Ashdod; their bodies are contorted in agony or limp in the stillness of death, illustrating the mercilessness of the affliction. The variety of postures and expressions captures the range of human suffering and chaos that accompanies such disaster.
Amongst the afflicted, several figures stand out due to their dynamic gestures or central placement within the composition, drawing the viewer’s eye and emphasizing the emotional impact of the scene. In the background, classical architecture gives a sense of order and permanence that starkly contrasts with the disarray and despair of the figures. Poussin’s use of colour and light skilfully highlights the drama, with the dark and earthy tones of the suffering masses set against the lighter, more serene sky, which suggests divine presence or intervention.
Poussin’s use of color and light skillfully highlights the drama, with the dark and earthy tones of the suffering masses set against the lighter, more serene sky, which suggests divine presence or intervention. The overall effect is one of a carefully structured scene that conveys a narrative full of intensity and profound human drama, characteristic of the religious paintings of the period and the classical style Poussin is renowned for. Poussin began to paint The Plague of Ashdod while the bubonic plague was still raging throughout Italy though sparing Rome. He first called the painting The Miracle in the Temple of Dagon, but later it became known as The Plague of Ashdod.
The painting most importantly provides a view into how illness and diseases were feared at that time in the past and the fact that people had the knowledge that it was transmissible during that time period which was the 16th century.
Researchers from the Department of Clinical Medicine at Aarhus University have been able to demonstrate for the first time that the memstrual cycle affects a plethora of proteins in the female body. This is explored by one of the leading researchers who is behind the study – Jonas Ghouse. This study is published in the…
Theorising the medical philosophy This privileged relation between medicine and health involved the possibility of being one’s own physician. Nineteenth- century medicine, on the other hand, was regulated more in accordance with normality than with health; it formed its concepts and prescribed its interventions in relation to a standard of functioning and organic structure, and…
Determining the Common Ground for Tertiary Hospital Care The criticism levelled at hospital foundations was a common-place of eighteenth-century economic analysis. The funds on which they are based are, of course, inalienable: they are the perpetual due of the poor. But poverty is not perpetual; needs change, and assistance must be given to those provinces…
The research that I am undertaking here therefore involves a project that is deliberately both historical and critical, in that it is concerned—outside all prescriptive intent—with determining the conditions of possibility of medical experience in modern times. I should like to make it plain once and for all that this book has not been written…
I’m feeling overwhelmed with all the support and the love for this blog over the second year! I think brainstorming the relevant topics on medicine that don’t get scrutinisingly covered in medical school is what makes this blog such a hit! Its what I love about the blog too! I think of all those years…
Some treat their curing work as a divine calling; others seem more like pragmatic businessmen. Yet, there are striking similarities in the paths that led these exceptional individuals to the occupation of curandero, and there is an underlying curing philosophy that unites them. Our primary objective is ethnographic, to record in detail the symbolic system…
Researchers from the Department of Clinical Medicine at Aarhus University have been able to demonstrate for the first time that the memstrual cycle affects a plethora of proteins in the female body. This is explored by one of the leading researchers who is behind the study – Jonas Ghouse. This study is published in the journal Nature Medicine.
“The study shows that the body’s building blocks—proteins, change to a far greater extent during the menstrual cycle than previously recognized,” he says. Researchers have identified close to 200 proteins that change in its entirety throughout the menstrual cycle.
Several of these proteins are found to have been linked to conditions such as ednometriosis, uterine fibroids, and bleeding disorders. Nearly 3,000 plasma proteins from 2,760 women’s health data from the UK Biobank were profiled on and 198 varying proteins across the menstrual cycle were identified. This study was carried out in younger and older women. These formed distinct temporal patterns that aligned with their corresponding menstrual phases. These proteins include reproductive hormones, cytokines and growth factors, many of which are enriched in endometrial tissue and expressed in epithelial and stromal cell types, highlighting their biological specificity. Several proteins were linked to common reproductive disorders, including endometriosis, leiomyoma and abnormal bleeding. Finally, we developed a proteomic score on the basis of 75 proteins that accurately predicts menstrual cycle phase.
These findings can help provide a menstrual cycle atlas on a systematic level and keep informed of biomarkers essential to a women’s health.
a, A volcano plot of associations between circulating protein levels and menstrual cycle day in all women (N = 2,760). b, A volcano plot in women ≤45 years (N = 1,421). c, A volcano plot in women >45 years (N = 1,339). In a–c, each point represents one protein, with the x axis showing the normalized protein expression (NPX) value (s.d. units) from the linear regression model and the y axis showing the −log10 P value (two-sided). The red points indicate proteins positively associated with cycle day, and the blue points indicate proteins negatively associated with cycle day, at an FDR < 0.05. P values were corrected for multiplicity using Benjamini–Hochberg correction. Analyses were adjusted for age, BMI, smoking status, self-reported ancestry, time between blood draw and proteomic measurement, and batch. Top associations are annotated on the plot. d, A comparison of effect estimates for protein–cycle day associations between younger and older women. Each point represents a protein, with x- and y axes showing the estimated regression coefficients in younger and older women, respectively. The dashed line indicates the reference line, and the solid line represents the fit linear regression. e, The distribution of variance explained (R2) by cycle day, BMI and age from separate natural cubic spline models. The dashed line marks R2 of 0.05. The points and labels denote the top five proteins per predictor. f, The number of proteins with R2 > 0.05 from the same spline models.a, The distribution of prevalent (red) and incident (blue) diagnoses among women in the UKB cohort with available proteomics data (N = 23,674). b, Protein-prevalent disease associations (FDR < 0.05) across 12 reproductive health conditions. The dot size indicates absolute effect size (logOR per s.d. increase in protein level), and the colors represent −log10P (two-sided). c, The protein–incident disease associations (FDR < 0.05) across eight conditions, with dot size and color as in b. In b and c, protein–disease associations were estimated using logistic regression models adjusted for age, BMI, smoking status, self-reported ancestry, time between blood draw and proteomic measurement, and batch. P values were corrected for multiplicity using Benjamini–Hochberg correction.
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