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Preview: /Review: Michael Webb, The Whole at Once: A Conversation on Meaning (Austin,TX: Fire Hill Press, 2020), 244 pages./ This is a book about a phenomenological challenge: to reach the depths of meaning. It relies principally on becoming aware of the self and of the core essence of wholes, be they collections of objects or sentences or ideas. But meaning is the end point constituting, according to the author, a drive more powerful even than the will to live (WO, 137). It lies beyond any given perspective. The work is presented as a dialogue between student and master; its 244 pages actually make for a quick and relatively easy read, not burdening the reader with jargon. It intends to be a popular presentation but without skimping on issues of relevance to philosophy.

David Graeber wrote about debt, jobs and the negative effects of globalization. He was an American anthropologist, anarchist activist, and was an author known for his books Debt: The First 5000 Years, The Utopia of Rules and Bullshit Jobs: A Theory. A professor of anthropology at the London School of Economics, he passed away 2 September 2020, at age 59.

This work shows the construction of a simple, functional and real-time application to estimate the population dynamics of the Golden Mussel, an invasive species that has been causing great ecological and economic damage, particularly to the electricity sector by obstructing water collection routes of hydroelectric plant equipment. The tool Golden Mussel App, developed with Shiny package of the R©, programming language, aims to enable professionals engaged in harm reduction in the energy generation sector to follow the temporal evolution of populations, even without advanced knowledge about the mathematical modeling of the problem. In this way, the application configures itself as an auxiliary tool in the planning of actions to control the Golden Mussel

BACKGROUND:. Surrogate decision-making is a stressful process for many family members of critically ill patients. The COVID-19 pandemic may have amplified the risk for anxiety, depression, and posttraumatic stress disorder (PTSD) symptoms in ICU surrogates. OBJECTIVES:. This study piloted an online group-based behavioral intervention with family members of deceased COVID-19 patients. Participant engagement, perceptions, and responses related to the intervention were assessed. DESIGN:. A single-arm pilot study was conducted with bereaved families. Quantitative analysis of measures of anxiety, depression, and PTSD symptoms was conducted with mixed models. Qualitative data were analyzed to identify themes in surrogates’ experiences with the intervention. SETTING:. Participants were recruited from ICUs at a tertiary academic medical center. Participants completed the intervention, measures, and interviews online. SUBJECTS:. Participants were family members of patients who died from COVID-19. INTERVENTIONS:. The intervention involved six online group-based behavioral activation sessions. Sessions covered topics pertinent to grieving and engagement in personally meaningful activities. MEASUREMENTS AND MAIN RESULTS:. Semi-structured interviews explored participants’ experiences with the intervention. Surrogates also completed measures of anxiety, depression, and PTSD symptoms before and after the intervention. Nineteen of 26 participants (73.1%) completed the study. Thematic analysis suggested that surrogates found the group helpful for overcoming perceived isolation, receiving validation, and developing coping skills. Significant pre-to-post reductions were observed in symptoms of Hospital and Anxiety Disorder Scale (HADS) anxiety (pre-mean = 9.27, sd = 5.30 vs post-mean = 6.80, sd = 4.16; p = 0.0271), HADS depression (pre-mean =6 .65, sd = 4.58 vs post- mean = 4.89, sd = 3.40; p = 0.0436), and Impact of Events Scale-Revised PTSD (pre-mean = 36.86, sd = 16.97 vs post-mean = 24.14, sd = 13.49; p = 0.0008). LIMITATIONS:. This was a preliminary study based on qualitative and self-report measures. Future studies should include a control group. CONCLUSIONS:. Online group-based behavioral activation therapy appears to be a potentially useful intervention for family members of ICU patients who died from COVID-19.

Multiple myeloma (MM) is a hematologic cancer characterized by accumulation of malignant plasma cells in the bone marrow. To date, no definitive cure exists for MM and resistance to current treatments is one of the major challenges of this disease. The DNA helicase BLM, whose depletion or mutation causes the cancer-prone Bloom’s syndrome (BS), is a central factor of DNA damage repair by homologous recombination (HR) and genomic stability maintenance. Using independent cohorts of MM patients, we identified that high expression of BLM is associated with a poor outcome with a significant enrichment in replication stress signature. We provide evidence that chemical inhibition of BLM by the small molecule ML216 in HMCLs (human myeloma cell lines) leads to cell cycle arrest and increases apoptosis, likely by accumulation of DNA damage. BLM inhibition synergizes with the alkylating agent melphalan to efficiently inhibit growth and promote cell death in HMCLs. Moreover, ML216 treatment re-sensitizes melphalan-resistant cell lines to this conventional therapeutic agent. Altogether, these data suggest that inhibition of BLM in combination with DNA damaging agents could be of therapeutic interest in the treatment of MM, especially in those patients with high BLM expression and/or resistance to melphalan.

The COVID-19 pandemic has led health schools to cancel many on-site training and exams. Teachers were looking for the best option to carry out online OSCEs, and Zoom was the obvious choice since many schools have used it to pursue education purposes. Methods: We conducted a feasibility study during the 2020–2021 college year divided into six pilot phases and the large-scale eOSCEs on Zoom on June 30th, 2021. We developed a specific application allowing us to mass create Zoom meetings and built an entire organization, including a technical support system (an SOS room and catching-up rooms) and teachers’ training sessions. We assessed satisfaction via an online survey. Results: On June 30th, 531/794 fifth-year medical students (67%) participated in a large-scale mock exam distributed in 135 Zoom meeting rooms with the mobilization of 298 teachers who either participated in the Zoom meetings as standardized patients (N =135, 45%) or examiners (N =135, 45%) or as supervisors in the catching-up rooms (N =16, 6%) or the SOS room (N =12, 4%). In addition, 32/270 teachers (12%) experienced difficulties connecting to their Zoom meetings and sought the help of an SOS room member. Furthermore, 40/531 students (7%) were either late to their station or had technical difficulties and declared those issues online and were welcomed in one of the catching-up rooms to perform their eOSCE stations. Additionally, 518/531 students (98%) completed the entire circuit of three stations, and 225/531 students (42%) answered the online survey. Among them, 194/225 (86%) found eOSCES helpful for training and expressed their satisfaction with this experience. Conclusion: Organizing large-scale eOSCEs on Zoom is feasible with the appropriate tools. In addition, eOCSEs should be considered complementary to on-site OSCEs and to train medical students in telemedicine.

Introduction This study aims to measure how transmission of SARS-CoV-2 occurs in communities and to identify conditions that lend to increased transmission focusing on congregate situations. We will measure SARS-CoV-2 in exhaled breath of asymptomatic and symptomatic persons using face mask sampling—a non-invasive method for SARS-CoV-2 detection in exhaled air. We aim to detect transmission clusters and identify risk factors for SARS-CoV-2 transmission in presymptomatic, asymptomatic and symptomatic individuals.Methods and analysis In this observational prospective study with daily follow-up, index cases and their respective contacts are identified at each participating institution. Contact definitions are based on Centers for Disease Control and Prevention and local health department guidelines. Participants will wear masks with polyvinyl alcohol test strips adhered to the inside for 2 hours daily. The strips are applied to all masks used over at least 7 days. In addition, self-administered nasal swabs and (optional) finger prick blood samples are performed by participants. Samples are tested by standard PCR protocols and by novel antigen tests.Ethics and dissemination This study was approved by the Colorado Multiple Institutional Review Board and the WHO Ethics Review Committee. From the data generated, we will analyse transmission clusters and risk factors for transmission of SARS-CoV-2 in congregate settings. The kinetics of asymptomatic transmission and the evaluation of non-invasive tools for detection of transmissibility are of crucial importance for the development of more targeted control interventions—and ultimately to assist with keeping congregate settings open that are essential for our social fabric.Trial registration number ClinicalTrials.gov (#NCT05145803).

Active learning pedagogies are shown to enhance the outcomes of students, particularly in disciplines known for high attrition rates. Despite the demonstrated benefits of active learning, didactic lecture continues to predominate in science, technology, engineering, and mathematics (STEM) courses. Change agents and professional development programs have historically placed emphasis on develop–disseminate efforts for the adoption of research-based instructional strategies (RBIS). With numerous reported barriers and motivators for trying out and adopting active learning, it is unclear to what extent these factors are associated with adoption of RBIS and the effectiveness of change strategies. We present the results of a large-scale, survey-based study of introductory chemistry, mathematics, and physics instructors and their courses in the United States. Herein, we evaluate the association of 17 malleable factors with the tryout and adoption of RBIS. Multilevel logistic regression analyses suggest that several contextual, personal, and teacher thinking factors are associated with different stages of RBIS adoption. These results are also compared with analogous results evaluating the association of these factors with instructors’ time spent lecturing. We offer actionable implications for change agents to provide targeted professional development programming and for institutional leaders to influence the adoption of active learning pedagogies in introductory STEM courses.

This study investigated whether heat treatments (raw, 63 °C for 30 min, and 85 °C for 5 min) affect protein hydrolysis by endogenous enzymes in the milk of ruminants (bovine, ovine, and caprine) using a self-digestion model. Self-digestion consisted of the incubation for six hours at 37 °C of the ruminants’ milk. Free amino group concentration was measured by the o-phthaldialdehyde method, and peptide sequences were identified by chromatography-mass spectrometry. Results showed that heat treatments prior to self-digestion decreased the free NH2 by 59% in bovine milk heated at 85 °C/5 min, and by 44 and 53% in caprine milk heated at 63 °C/30 min and 85 °C/5 min, respectively. However, after self-digestion, only new free amino groups were observed for the raw and heated at 63 °C/30 min milk. β-Casein was the most cleaved protein in the raw and heated at 63 °C/30 min bovine milk. A similar trend was observed in raw ovine and caprine milk. Self-digestion increased 6.8-fold the potential antithrombin peptides in the bovine milk heated at 63 °C/30 min. Enhancing bioactive peptide abundance through self-digestion has potential applications in the industry for functional products. Overall, heat treatments affected the free amino groups according to the species and heat treatment applied, which was reflected in the varying degrees of cleaved peptide bonds and peptides released during self-digestion.

Abstract Sepsis is a major cause of mortality among hospitalized patients worldwide. Shorter time to administration of broad‐spectrum antibiotics is associated with improved outcomes, but early recognition of sepsis remains a major challenge. In a two‐center cohort study with prospective sample collection from 1400 adult patients in emergency departments suspected of sepsis, we sought to determine the diagnostic and prognostic capabilities of a machine‐learning algorithm based on clinical data and a set of uncommonly measured biomarkers. Specifically, we demonstrate that a machine‐learning model developed using this dataset outputs a score with not only diagnostic capability but also prognostic power with respect to hospital length of stay (LOS), 30‐day mortality, and 3‐day inpatient re‐admission both in our entire testing cohort and various subpopulations. The area under the receiver operating curve (AUROC) for diagnosis of sepsis was 0.83. Predicted risk scores for patients with septic shock were higher compared with patients with sepsis but without shock (p