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Sensors embedded in smartphones allow for the passive momentary quantification of people's states in the context of their daily lives in real time. Such data could be useful for alleviating the burden of ecological momentary assessments and increasing utility in clinical assessments. Despite existing research on using passive sensor data to assess participants' moment-to-moment states and activity levels, only limited research has investigated temporally linking sensor assessment and self-reported assessment to further integrate the 2 methodologies. We investigated whether sparse movement-related sensor data can be used to train machine learning models that are able to infer states of individuals' work-related rumination, fatigue, mood, arousal, life engagement, and sleep quality. Sensor data were only collected while the participants filled out the questionnaires on their smartphones. We trained personalized machine learning models on data from employees (N=158) who participated in a 3-week ecological momentary assessment study. The results suggested that passive smartphone sensor data paired with personalized machine learning models can be used to infer individuals' self-reported states at later measurement occasions. The mean R was approximately 0.31 (SD 0.29), and more than half of the participants (119/158, 75.3%) had an R of ≥0.18. Accuracy was only slightly attenuated compared with earlier studies and ranged from 38.41% to 51.38%. Personalized machine learning models and temporally linked passive sensing data have the capability to infer a sizable proportion of variance in individuals' daily self-reported states. Further research is needed to investigate factors that affect the accuracy and reliability of the inference.

FLASH radiotherapy is an emerging technique in radiation oncology that may improve clinical outcomes by reducing normal tissue toxicities. The physical radiation characteristics needed to induce the radiobiological benefits of FLASH are still an active area of investigation. To determine the dose rate, range of doses and delivery time structure necessary to trigger the FLASH effect, Drosophila melanogaster were exposed to ultrahigh dose rate (UHDR) or conventional radiotherapy dose rate (CONV) 120-kVp X-rays. A conventional X-ray tube outfitted with a shutter system was used to deliver 17- to 44-Gy doses to third-instar D. melanogaster larvae at both UHDR (210 Gy/s) and CONV (0.2–0.4 Gy/s) dose rates. The larvae were then tracked through development to adulthood and scored for eclosion and lifespan. Larvae exposed to UHDR eclosed at higher rates and had longer median survival as adults compared to those treated with CONV at the same doses. Eclosion rates at 24 Gy were 68% higher for the UHDR group (P < 0.05). Median survival from 22 Gy was >22 days for UHDR and 17 days for CONV (P < 0.01). Two normal tissue-sparing effects were observed for D. melanogaster irradiated with UHDR 120-kVp X-rays. The effects appeared only at intermediate doses and may be useful in establishing the dose range over which the benefits of FLASH can be obtained. This work also demonstrates the usefulness of a high-throughput fruit fly model and a low-cost X-ray tube system for radiobiological FLASH research.

The early conversations on social media by emergency physicians offer a window into the ongoing response to the COVID-19 pandemic. This retrospective observational study of emergency physician Twitter use details how the health care crisis has influenced emergency physician discourse online and how this discourse may have use as a harbinger of ensuing surge. Followers of the three main emergency physician professional organizations were identified using Twitter's application programming interface. They and their followers were included in the study if they identified explicitly as US-based emergency physicians. Statuses, or tweets, were obtained between January 4, 2020, when the new disease was first reported, and December 14, 2020, when vaccination first began. Original tweets underwent sentiment analysis using the previously validated Valence Aware Dictionary and Sentiment Reasoner (VADER) tool as well as topic modeling using latent Dirichlet allocation unsupervised machine learning. Sentiment and topic trends were then correlated with daily change in new COVID-19 cases and inpatient bed utilization. A total of 3463 emergency physicians produced 334,747 unique English-language tweets during the study period. Out of 3463 participants, 910 (26.3%) stated that they were in training, and 466 of 902 (51.7%) participants who provided their gender identified as men. Overall tweet volume went from a pre-March 2020 mean of 481.9 (SD 72.7) daily tweets to a mean of 1065.5 (SD 257.3) daily tweets thereafter. Parameter and topic number tuning led to 20 tweet topics, with a topic coherence of 0.49. Except for a week in June and 4 days in November, discourse was dominated by the health care system (45,570/334,747, 13.6%). Discussion of pandemic response, epidemiology, and clinical care were jointly found to moderately correlate with COVID-19 hospital bed utilization (Pearson r=0.41), as was the occurrence of \"covid,\" \"coronavirus,\" or \"pandemic\" in tweet texts (r=0.47). Momentum in COVID-19 tweets, as demonstrated by a sustained crossing of 7- and 28-day moving averages, was found to have occurred on an average of 45.0 (SD 12.7) days before peak COVID-19 hospital bed utilization across the country and in the four most contributory states. COVID-19 Twitter discussion among emergency physicians correlates with and may precede the rising of hospital burden. This study, therefore, begins to depict the extent to which the ongoing pandemic has affected the field of emergency medicine discourse online and suggests a potential avenue for understanding predictors of surge.

International humanitarian aid during disasters should be needs-based and coordinated in response to appeals from affected governments. We identify disaster and population factors associated with international aid appeal during disasters and hence guide preparation by international humanitarian aid providers. In this retrospective database analysis, we searched the Emergency Events Database for all disasters from 1995 to 2015. Disasters with and without international aid appeals were compared by location, duration, type of disaster, deaths, number of people affected, and total estimated damage. Logistic regression was used to examine the association of each factor with international aid appeal. Of 13,961 disasters recorded from 1995 to 2015, 168 (1.2%) involved international aid appeals. Aid appeals were more likely to be triggered by disasters which killed more people (OR 1.29 [95% confidence interval (CI) 1.02-1.64] log10 persons), affected more people (OR 1.85 [95%CI 1.57-2.18] / log10 persons), and occurred in Africa (OR 1.67 [95%CI 1.06-2.62). Earthquakes (OR 4.07 [95%CI 2.16-7.67]), volcanic activity (OR 6.23 [95%CI 2.50-15.53]), and insect infestations (OR 12.14 [95%CI 3.05-48.35]) were more likely to trigger international aid appeals. International aid appeals were less likely to be triggered by disasters which occurred in Asia (OR 0.46 [95%CI 0.29-0.73]) and which were transport accidents (OR 0.12 [95%CI 0.02-0.89]). International aid appeal during disasters was associated with greater magnitude of damage, disasters in Africa, and specific types of disasters such as earthquakes, volcanic activity, and insect infestations. Humanitarian aid providers can focus preparation on these identified factors.

Diatoms, a major group of microalgae, play a critical role in global carbon cycling and primary production. Despite their ecological significance, comprehensive genomic resources for diatoms are limited. To address this, we have annotated previously unannotated genome assemblies of 49 diatom species. Genome assemblies were obtained from NCBI Datasets and processed for repeat elements using RepeatModeler2 and RepeatMasker. For gene prediction, BRAKER2 was employed in the absence of transcriptomic data, while BRAKER3 was utilised when transcriptome short read data were available from the Sequence Read Archive. The quality of genome assemblies and predicted protein sets was evaluated using BUSCO, ensuring high-quality genomic resources. Functional annotation was performed using EnTAP, providing insights into the biological roles of the predicted proteins. Our study enhances the genomic toolkit available for diatoms, facilitating future research in diatom biology, ecology, and evolution.

Background: Men with chronic scrotal content pain (CSCP) commonly present to various providers within the healthcare system. Despite its prevalence, little research has been done to understand risk factors for the development of CSCP. In many cases, the cause of pain is unknown, and there are no widely accepted protocols for evaluation or management. Objective: To characterize associated symptoms and concomitant concerns of those presenting with CSCP. Design and methods: Retrospective review of validated questionnaires including the Chronic Orchialgia Symptom Index (COSI), the internal index of erectile function, the NIH-chronic prostatitis symptom index, the American Urological Association symptom index/international prostate symptom score, the hip dysfunction and osteoarthritis outcome score, the Oswestry low back pain questionnaire, the patient health questionnaire-9, the general anxiety disorder-7, and a comprehensive intake form on men presenting to a single urologist’s office with CSCP was performed. The analysis included constructing linear best-fit lines between subjective chronic testicular pain rating and other numerical rating scales. Results: Questionnaires from 94 male patients were reviewed. The average pain subscore on the COSI was 8.00 out of 17. When assessing the association between pain and other domains, more severe chronic scrotal pain was associated with worse pain in and around the genitourinary system (p < 0.001), worse urinary symptoms (p = 0.001), worse hip (p = 0.001) and back (p < 0.001) symptoms, worse sexual function (p = 0.025), and worse anxiety (p = 0.019) and depression (p = 0.003) symptoms. Patients in our study were found to have a wide variety of presentations with differing aggravating and relieving factors, urological and surgical histories, and interventions. Conclusion: Men presenting with CSCP may present with many co-occurring symptoms. More severe scrotal content pain may be associated with worse symptoms in multiple other domains. In order to create a personalized treatment plan, a more comprehensive understanding of these men is critical. Future studies should focus on further developing a standardized approach for assessing these patients and how directed interventions on associated symptoms may impact outcomes.

BackgroundThe number of residency applications submitted by medical students has risen at an alarming rate, causing increased cost of applications and subsequent interview travel. These both contribute to increased cost for medical students. In light of these concerns, specialty governing bodies have proposed ideas to fight these trends including, application limits, interview limits, using a preference signaling system, and continuing virtual interviews. During the Covid-19 pandemic, all residency interviews were performed virtually, essentially making travel expenses negligible. However, this created a new concern with regards to assessing program and applicant compatibility, as compared to in-person interactions and did nothing to combat the increases in application numbers. Therefore, we want to critically assess the effects of virtual interviews on number of applications submitted, number of interview invites received, and number of interviews attended. We also aim to analyze how applicants viewed the virtual process.Methods600 medical students were eligible to participate. 456 students from years 2018-2020 were eligible to be surveyed following the NRMP match. 144 students were eligible to be surveyed following 2021 NRMP match. The survey was distributed to medical school graduates just prior to graduation and asked how many programs each student applied to, how many interview invites they received, and how many interviews they attended. The 2021 survey also asked, “How did virtual interviews affect your interview experience?” The quantitative results were compared with student's t-test and qualitative results are presented below. ResultsThe average number of programs each applicant applied to increased from 35.4 to 47.7 (p-value=0.002) when residency interviews switched from in-person to virtual. However, interview invites received and interviews attended did not change (16.8 vs 16.3, p-value=0.91, 11.8 vs 12.7, p-value=0.18). There were 188 participants in the in-person interview group (response rate=41.2%) and 128 participants in the virtual interview group (response rate=83.3%). The standard deviation and range also increased for number of applications, number of interview invites received, and number of interviews attended. There were 123 responses to the free response question. 36 had a positive experience, 44 were neutral, 47 were negative. The positive themes included 15 noted less expenses, 18 noted more convenient/less time, and 18 were able to attend more interviews. Negative themes included, 38 noted difficulty assessing program fit, 19 wanted to see the program or city in person, eight had increased interest in home/local programs, six found it difficult to make connections or stand out. ConclusionSixty-three percent of students reported a positive or neutral experience with virtual interviews. Students applied to more programs when interviews were virtual, but did not receive more interview invites or attend more interviews. These results suggest that virtual interviews are sufficient to conduct residency interviews, however the number of applications continues to rise with no increase in the number interview invites received or number of interviews attended. The increase in the standard deviation and range for all three variables may point to some applicants being able to get more invites and attend more interviews leaving less available spots for other applicants.

[...]there have been calls for changes to Australia's disaster management system and specifically for greater involvement of the Australian Defense Force (ADF) to combat this existential national security threat [1]. The Australian bushfires as well as the COVID-19 pandemic have exposed a number of issues: the lack of involvement of primary healthcare workers in all phases of the disaster cycle, limited access to disaster zones, fragmented coordination and redistribution of the healthcare workforce, as well as a lack of surge coordination, especially within the private sector, which houses 35% of Australia's intensive care beds. A surge-capable, on demand healthcare workforce that is trained in disaster response could also serve as local community leaders in disaster preparedness during normal operational periods, and fill an education gap in their local communities.

Perception of weight loss requirements before bariatric surgery varies among patients, physicians, and health insurance payers. Current clinical guidelines do not require preoperative weight loss because of a lack of scientific support regarding its benefits. To examine the association of preoperative body mass index (BMI) and weight loss with 30-day mortality after bariatric surgery. This cohort study used data from 480 075 patients who underwent bariatric surgery from 2015 to 2017 in the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program, which covers more than 90% of all bariatric surgery programs in the United States and Canada. Clinical and demographic data were collected at all participating institutions using a standardized protocol. Data analysis was performed from December 2018 to November 2019. Preoperative BMI and weight loss. 30-day mortality after bariatric surgery. Of the 480 075 patients (mean [SD] age 45.1 [12.0] years; 383 265 [79.8%] women), 511 deaths (0.1%) occurred within 30 days of bariatric surgery. Compared with patients with a preoperative BMI of 35.0 to 39.9, the multivariable-adjusted odds ratios for 30-day mortality for patients with preoperative BMI of 40.0 to 44.9, 45.0 to 49.9, 50.0 to 54.9, and 55.0 and greater were 1.37 (95% CI, 1.02-1.83), 2.19 (95% CI, 1.64-2.92), 2.61 (95% CI, 1.90-3.58), and 5.03 (95% CI, 3.78-6.68), respectively (P for trend < .001). Moreover, compared with no preoperative weight loss, the multivariable-adjusted odds ratios for 30-day mortality for patients with weight loss of more than 0% to less than 5.0%, 5.0% to 9.9%, and 10.0% and greater were 0.76 (95% CI, 0.60-0.96), 0.69 (95% CI, 0.53-0.90), and 0.58 (95% CI, 0.41-0.82), respectively (P for trend = .003). In this study, even moderate weight loss (ie, >0% to <5%) before bariatric surgery was associated with a lower risk of 30-day mortality. These findings may help inform future updates of clinical guidelines regarding bariatric surgery.

The Sendai Framework for Disaster Risk Reduction 2015–2030 placed human health at the centre of disaster risk reduction, calling for the global community to enhance local and national health emergency and disaster risk management (Health EDRM). The Health EDRM Framework, published in 2019, describes the functions required for comprehensive disaster risk management across prevention, preparedness, readiness, response, and recovery to improve the resilience and health security of communities, countries, and health systems. Evidence-based Health EDRM workforce development is vital. However, there are still significant gaps in the evidence identifying common competencies for training and education programmes, and the clarification of strategies for workforce retention, motivation, deployment, and coordination. Initiated in June 2020, this project includes literature reviews, case studies, and an expert consensus (modified Delphi) study. Literature reviews in English, Japanese, and Chinese aim to identify research gaps and explore core competencies for Health EDRM workforce training. Thirteen Health EDRM related case studies from six WHO regions will illustrate best practices (and pitfalls) and inform the consensus study. Consensus will be sought from global experts in emergency and disaster medicine, nursing, public health and related disciplines. Recommendations for developing effective health workforce strategies for low- and middle-income countries and high-income countries will then be disseminated.