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Bart Haagmans (Erasmus MC) concludes: "The observations made in this study provide definite proof that SARS-CoV-2 can multiply in cells of the gastrointestinal tract. However, we don't yet know whether SARS-CoV-2, present in the intestines of COVID-19 patients, plays a significant role in transmission. Our findings indicate that we should look into this possibility more closely." The current study is in line with other recent studies that identified gastrointestinal symptoms in a large fraction of COVID-19 patients and virus in the stool of patients free of respiratory symptoms. Special attention may be needed for those patients with gastrointestinal symptoms. More extensive testing using not only nose and throat swabs, but also rectal swabs or stool samples may thus be needed.

"With each interaction, Alexa is training to hear better, to interpret more precisely, to trigger actions that map to the user's commands more accurately, and to build a more complete model of their preferences, habits and desires. What is required to make this possible? Put simply: each small moment of convenience - be it answering a question, turning on a light, or playing a song - requires a vast planetary network, fueled by the extraction of non-renewable materials, labor, and data. The scale of resources required is many magnitudes greater than the energy and labor it would take a human to operate a household appliance or flick a switch. A full accounting for these costs is almost impossible, but it is increasingly important that we grasp the scale and scope if we are to understand and govern the technical infrastructures that thread through our lives. III The Salar, the world's largest flat surface, is located in southwest Bolivia at an altitude of 3,656 meters above sea level. It is a high plateau, covered by a few meters of salt crust which are exceptionally rich in lithium, containing 50% to 70% of the world's lithium reserves. 4 The Salar, alongside the neighboring Atacama regions in Chile and Argentina, are major sites for lithium extraction. This soft, silvery metal is currently used to power mobile connected devices, as a crucial material used for the production of lithium-Ion batteries. It is known as 'grey gold.' Smartphone batteries, for example, usually have less than eight grams of this material. 5 Each Tesla car needs approximately seven kilograms of lithium for its battery pack. 6 All these batteries have a limited lifespan, and once consumed they are thrown away as waste. Amazon reminds users that they cannot open up and repair their Echo, because this will void the warranty. The Amazon Echo is wall-powered, and also has a mobile battery base. This also has a limited lifespan and then must be thrown away as waste. According to the Ay

Thousands of different genetic mutations have been implicated in cancer, but a new analysis of almost 10,000 patients found that regardless of the cancer's origin, tumors could be stratified in only 112 subtypes and that, within each subtype, the Master Regulator proteins that control the cancer's transcriptional state were virtually identical, independent of the specific genetic mutations of each patient.

Younger generations are blamed for the pandemic's spread, but also face the brunt of the transmission risk that comes with keeping the economy going. 6 MINUTE READ BY REBECCA RENNER PUBLISHED SEPTEMBER 17, 2020 WHEN PARAMEDICS RUSHED the pregnant Honduran woman into the emergency room, 28-year-old Chuan-Jay Jeffrey Chen stood ready to receive her. It was April, and the pandemic had already taken over his final year as an emergency medicine resident. Of all the coronavirus patients surging into Massachusetts General Hospital in Boston, this 32-year-old patient remains Chen's most memorable. The woman was so short of breath she could barely speak, so Chen would need to intubate her-a tricky procedure that requires precision as well as speed. Every moment without oxygen causes a patient's chances of survival to decline; pregnancy further complicates the scenario by making airways swollen, causing blood pressure to drop more quickly. As Chen set to work and talked her through the steps in Spanish, he also tried to calm his own nerves. "I knew I had very little margin for error," says Chen. The woman's husband had been barred from entering the building because of coronavirus restrictionsgen-z

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in thousands of deaths in the world. Information about prediction model of prognosis of SARS-CoV-2 infection is scarce. We used machine learning for processing laboratory findings of 110 patients with SARS-CoV-2 pneumonia (including 51 non-survivors and 59 discharged patients). The maximum relevance minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator logistic regression model were used for selection of laboratory features. Seven laboratory features selected in the model were: prothrombin activity, urea, white blood cell, interleukin-2 receptor, indirect bilirubin, myoglobin, and fibrinogen degradation products. The signature constructed using the seven features had 98% [93%, 100%] sensitivity and 91% [84%, 99%] specificity in predicting outcome of SARS-CoV-2 pneumonia. Thus it is feasible to establish an accurate prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings.

The model, called Deep Claim, predicts both when and how much an insurance company will pay for a given claim in advance of any payment they make. It was trained with three million de-identified claims including parameters like demographic information, diagnoses, treatments, and billed amounts. Using this information, Deep Claim can not only predict the date and amount of payments with reasonable certainty, but also the likeliest reasonings for any claim denial in play.

"This is a wonderfully short and easy to read paper looking at how complex systems fail - it's written by a Doctor (MD) in the context of systems of patient care, but that makes it all the more fun to translate the lessons into complex IT systems, including their human operator components. The paper consists of 18 observations. Here are some of my favourites…."

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection platforms currently report qualitative results. However, technology based on RT-PCR allows for calculation of viral load, which is associated with transmission risk and disease severity in other viral illnesses.1 Viral load in COVID-19 might correlate with infectivity, disease phenotype, morbidity, and mortality. To date, no studies have assessed the association between viral load and mortality in a large patient cohort.2, 3, 4 To our knowledge, we are the first to report on SARS-CoV-2 viral load at diagnosis as an independent predictor of mortality in a large hospitalised cohort (n=1145).

The differing immune system responses of patients with COVID-19 can help predict who will experience moderate and severe consequences of disease, according to a new study by Yale researchers published July 27 in the journal Nature.

Given constant emergence of new infectious threats, Infectious Diseases (ID) should be one of the most attractive medical specialties to students and trainees. Yet, ID Fellowship programs continue to not fill in the match, and ID remains among the lowest paid specialties. Nearly 35 years after Dr. Petersdorf first asked the question, we find ourselves once again wondering, "Whither Infectious Diseases?" To answer this question, and align with predominant US market forces, ID experts should push for: 1) restrictions regarding utilization of ID diagnostics and antimicrobial agents; 2) pay-for-performance measures regarding antimicrobial prescribing rates; and 3) healthcare reform as called for by the American College of Physicians to move away from fee-for-service medicine. Einstein said, "Continuing to do the same thing over and over and expecting a different result is the definition of insanity." We must move towards alignment with market forces, to benefit our patients, society, and our colleagues.

Healthcare responses to the novel coronavirus may be hastening another long looming public health threat, writes Jeremy Hsu The global threat of antimicrobial resistant bacteria and other superbugs is worsening as many patients admitted to hospital with covid-19 receive antibiotics to keep secondary bacterial infections in check.

Though it may not be common knowledge, AI systems are currently being used in a wide variety of commercial applications, including article selection on news and social media sites, which movies get made,and maps that appear on our phones-AI systems have become trusted tools by big business. But their use has not always been without controversy. In recent years, researchers have found that AI apps used to approve mortgage and other loan applications are biased, for example, in favor of white males. This, researchers found, was because the dataset used to train the system mostly comprised white male profiles. In this new effort, the researchers wondered if the same might be true for AI systems used to assist doctors in diagnosing patients.

In December 2019, the Coronavirus disease 2019 (COVID-19), caused by a novel coronavirus SARS-CoV-2, emerged in Wuhan, Hubei province, China1 and soon spread across the world. In this ongoing pandemic, public health concerns and the urgent need for effective therapeutic measures require a deep understanding of its epidemiology, transmissibility and pathogenesis. Here we analyzed the clinical, molecular and immunological data from 326 confirmed cases of COVID-19 in Shanghai. Genomic sequences of SARS-CoV-2 assembled from 112 quality samples together with sequences in the Global Initiative on Sharing All Influenza Data (GISAID) showed a stable evolution and suggested two major lineages with differential exposure history during the early phase of the outbreak in Wuhan. Nevertheless, they exhibited similar virulence and clinical outcomes. Lymphocytopenia, especially the reduced CD4+ and CD8+ T cell counts upon admission, was predictive of disease progression. High levels of IL-6 and IL-8 during treatment were observed in patients with severe or critical disease and correlated with decreased lymphocyte count. The determinants of disease severity seemed to stem mostly from host factors such as age, lymphocytopenia, and its associated cytokine storm, whereas viral genetic variation did not significantly affect the outcomes.