Francis F. Maury, M.D. (1840 to 1879): an often forgotten pioneer in early American surgery.

Francis F. Maury (Fig. 1) was born on August 9, 1840, in Danville, Kentucky, where he was raised on a farm by his mother and father. His father was an Episcopal clergyman of Huguenot descent, whose forefathers had fled from France to escape religious persecution. After receiving a Bachelor of Arts degree from Center College in the summer of 1860, he entered medical school at the University of Virginia. After one full term, he matriculated to Philadelphia’s Jefferson Medical College and completed his medical education as a private student under the direction of Dr. Samuel D. Gross.1, 2 He obtained his Doctorate of Medicine in March of 1862 at the age of only 21 years. Such were his talents as a medical student that he was appointed resident physician at the Philadelphia Hospital one month before his graduation. Although he spent only one year there, he developed a reputation as a tireless, devoted, and charming surgeon. In April 1863, Maury was assigned to duty at the South Street General Hospital to serve as acting assistant surgeon in the U.S. Army for two years. In October 1863, he was appointed assistant professor to Dr. Gross and six months later became chief of Dr. Gross’ surgical clinic at Jefferson Medical College. In November 1865, at the age of only 25 years, he returned to the Philadelphia Hospital, where he was appointed one of the chief surgeons on the retirement of Dr. Gross from that institution. In April of 1866, Maury founded the Summer Course on Venereal and Cutaneous Diseases in the Jefferson Medical College, where he taught until his death.1 Although Maury did not consider himself a dermatologist, his expertise in this emerging field was widely recognized

Land Sparing Can Maintain Bird Diversity in Northeastern Bangladesh

One of humanity's most significant challenges in the process of attaining the established sustainability goals is balancing the growing human demand for food and the need to conserve biodiversity. This challenge requires appropriate land uses that are able to conserve biodiversity while ensuring ample food supply. This study compares bird species diversity and abundance in areas undergoing land sharing and land sparing in northeastern Bangladesh (West Bhanugach Reserved Forest). Birds serve as useful biologic indicators because of their presence within different trophic levels and their well-studied ecology. To survey birds, we selected a total of 66 sampling sites within land-sharing (33) and land-sparing (33) land-use areas. Between May and June 2017, we observed and recorded bird calls within a 50-m radius around each sampling site. We counted 541 individuals from 46 species of birds. The Shannon bird diversity was higher in the land-sparing sites (1.52) than in the land-sharing sites (1.23). We found approximately 30% more bird species (39 vs. 30) and 40% more individuals (318 vs. 223) in the land-sparing areas than land-sharing areas. Three bird species,Arachnothera longirostra,Micropternus brachyurusandCopsychus malabaricus, were significantly associated with the land-sparing sites. This study shows that land sharing negatively affects bird diversity, richness and abundance compared to land-sparing. The use of chemical fertilizers and the lack of food, such as insects, for birds can explain the lower diversity, richness and abundance of birds in the land-sharing areas. Although land sharing is an effective means of producing food, land sparing is the most effective land-use practice for preserving bird diversity in northeastern Bangladesh

30-Day Mortality and Cardiopulmonary Complication Rates in Patients Undergoing Emergency Surgery with Perioperative SARS-CoV-2 Infection

INTRODUCTION AND OBJECTIVE: Continued vigilance of operative outcomes in COVID-19 patients is important given the relative novelty of the SARS-CoV-2 infection. We sought to evaluate the 30-day mortality and cardiopulmonary complication rates in patients undergoing emergency surgery with perioperative COVID-19, in comparison to a control group of medically managed COVID-19 patients that did not require a surgical intervention. METHODS: A retrospective chart review at a single tertiary-care hospital in Michigan was undertaken. Patients who had tested positive for SARS-CoV-2 infection either 7 days before or within 30 days after surgery during March-May 2020 were included in the study (n=52). Propensity score matched (1:6) patients who had been positive for SARS CoV-2 infection during this time-period but did not undergo surgery served as controls (n=314). The primary endpoint was 30-day mortality. Secondary endpoints included cardiac and pulmonary complications. Multivariable logistic regression analyses were utilized to account for baseline differences. RESULTS: The 30-day mortality (17.3% vs 13.1%, p=0.408) and cardiac (28.9% vs 19.1%, p=0.107) and pulmonary complication (55.8% vs 49.4%, p=0.392) rates were similar in the surgical and the non-surgical groups. Multivariable analyses confirmed that emergency surgical intervention was not associated with increased odds for any of the studied adverse events (p\u3e0.10 for all 3 endpoints). CONCLUSIONS: Our analysis of 366 novel coronavirus patients demonstrates that patients undergoing emergency surgery with SARS-CoV-2 infection do not have an increased risk for 30-day mortality and cardiopulmonary complications compared to their counterparts that do not require surgery. The importance of this study is that an emergency intervention does not portend a poorer prognosis among patients with a confirmed SARS-CoV-2 Infection

Biomechanical Modeling of Brain Shift During Neurosurgery

https://openworks.mdanderson.org/sumexp22/1051/thumbnail.jp

COVID-19 impact on poultry production and distribution networks in Bangladesh

The COVID-19 pandemic has severely affected numerous economic sectors across the world, including livestock production. This study investigates how the pandemic has impacted the poultry production and distribution network (PDN), analyses stakeholders' changing circumstances, and provides recommendations for rapid and long-term resilience. This is based on a literature review, social media monitoring, and key informant interviews (n = 36) from across the poultry sector in Bangladesh. These included key informants from breeder farms and hatcheries, pharmaceutical suppliers, feed companies, dealers, farmers, middlemen, and vendors. We show that the poultry sector was damaged by the COVID-19 pandemic, partly as a result of the lockdown and also by rumors that poultry and their products could transmit the disease. This research shows that hardly any stakeholder escaped hardship. Disrupted production and transportation, declining consumer demand and volatile markets brought huge financial difficulties, even leading to the permanent closure of many farms. We show that the extent of the damage experienced during the first months of COVID-19 was a consequence of how interconnected stakeholders and businesses are across the poultry sector. For example, a shift in consumer demand in live bird markets has ripple effects that impact the price of goods and puts pressure on traders, middlemen, farmers, and input suppliers alike. We show how this interconnectedness across all levels of the poultry industry in Bangladesh makes it fragile and that this fragility is not a consequence of COVID-19 but has been revealed by it. This warrants long-term consideration beyond the immediate concerns surrounding the COVID-19 pandemic

The topology of a discussion: the #occupy case

We analyse a large sample of the Twitter activity developed around the social movement 'Occupy Wall Street' to study the complex interactions between the human communication activity and the semantic content of a discussion. We use a network approach based on the analysis of the bipartite graph @Users-#Hashtags and of its projections: the 'semantic network', whose nodes are hashtags, and the 'users interest network', whose nodes are users In the first instance, we find out that discussion topics (#hashtags) present a high heterogeneity, with the distinct role of the communication hubs where most the 'opinion traffic' passes through. In the second case, the self-organization process of users activity leads to the emergence of two classes of communicators: the 'professionals' and the 'amateurs'. Moreover the network presents a strong community structure, based on the differentiation of the semantic topics, and a high level of structural robustness when a certain set of topics are censored and/or accounts are removed. Analysing the characteristics the @Users-#Hashtags network we can distinguish three phases of the discussion about the movement. Each phase corresponds to specific moment of the movement: from declaration of intent, organisation and development and the final phase of political reactions. Each phase is characterised by the presence of specific #hashtags in the discussion. Keywords: Twitter, Network analysisComment: 13 pages, 9 figure

Modelling the transmission dynamics of H9N2 avian influenza viruses in a live bird market

H9N2 avian influenza viruses (AIVs) are a major concern for the poultry sector and human health in countries where this subtype is endemic. By fitting a model simulating H9N2 AIV transmission to data from a field experiment, we characterise the epidemiology of the virus in a live bird market in Bangladesh. Many supplied birds arrive already exposed to H9N2 AIVs, resulting in many broiler chickens entering the market as infected, and many indigenous backyard chickens entering with pre-existing immunity. Most susceptible chickens become infected within one day spent at the market, owing to high levels of viral transmission within market and short latent periods, as brief as 5.3 hours. Although H9N2 AIV transmission can be substantially reduced under moderate levels of cleaning and disinfection, effective risk mitigation also requires a range of additional interventions targeting markets and other nodes along the poultry production and distribution network

Prediction of Liver Regeneration Post-Radiotherapy Using Machine Learning and Deep Learning Models

Department of Imaging Physics Radiation Oncology Interventional Radiologyhttps://openworks.mdanderson.org/sumexp22/1136/thumbnail.jp

EPINEST, an agent-based model to simulate epidemic dynamics in large-scale poultry production and distribution networks

The rapid intensification of poultry production raises important concerns about the associated risks of zoonotic infections. Here, we introduce EPINEST (EPIdemic NEtwork Simulation in poultry Transportation systems): an agent-based modelling framework designed to simulate pathogen transmission within realistic poultry production and distribution networks. We provide example applications to broiler production in Bangladesh, but the modular structure of the model allows for easy parameterization to suit specific countries and system configurations. Moreover, the framework enables the replication of a wide range of eco-epidemiological scenarios by incorporating diverse pathogen life-history traits, modes of transmission and interactions between multiple strains and/or pathogens. EPINEST was developed in the context of an interdisciplinary multi-centre study conducted in Bangladesh, India, Vietnam and Sri Lanka, and will facilitate the investigation of the spreading patterns of various health hazards such as avian influenza, Campylobacter, Salmonella and antimicrobial resistance in these countries. Furthermore, this modelling framework holds potential for broader application in veterinary epidemiology and One Health research, extending its relevance beyond poultry to encompass other livestock species and disease systems