Uncommon presentations of type A quadricuspid aortic valve in the Septuagenarian.

BACKGROUND: Quadricuspid aortic valve (QAV) is a rare congenital anomaly characterized by the presence of four cusps instead of the usual three. It is estimated to occur in less than 0.05% of the population, with Type A (four equal-sized leaflets) accounting for roughly 30% of QAV subtypes. Based on limited clinical series, the usual presentation is progressive aortic valve regurgitation (AR) with symptoms occurring in the fourth to sixth decade of life. Severe aortic valve stenosis (AS) and acute AR are very uncommon. CASE PRESENTATION: We describe two cases of Type A QAV in patients who remained asymptomatic until their seventies with very uncommon presentations: one with severe AS and one with acute, severe AR and flail leaflet. In Case A, a 72-year-old patient with history of moderate AS presents to clinic with progressive exertional dyspnea. During work-up for transcatheter vs. surgical replacement pre-operative computed tomography angiogram (CTA) reveals a quadricuspid aortic valve with severe AS, and the patient undergoes surgical aortic valve replacement. Pre-discharge transthoracic echocardiography (TTE) shows good prosthetic valve function with no gradient or regurgitation. In Case B, a 76-year-old patient is intubated upon arrival to the hospital for acute desaturation, found to have wide open AR on catheterization, and transferred for emergent intervention. Intraoperative TEE reveals QAV with flail leaflet and severe AR. Repair is considered but deferred ultimately due to emergent nature. Post-operative TTE demonstrates good prosthetic valve function with no regurgitation and normal biventricular function. CONCLUSIONS: QAV can present as progressive severe AS and acute AR, with symptoms first occurring in the seventh decade of life. The optimal treatment for QAV remains uncertain. Although aortic valve repair or transcatheter option may be feasible in some patients, aortic valve replacement remains a tenable option.

A metagenomic analysis of the phase 2 Anopheles gambiae 1000 genomes dataset reveals a wide diversity of cobionts associated with field collected mosquitoes.

The Anopheles gambiae 1000 Genomes (Ag1000G) Consortium previously utilized deep sequencing methods to catalogue genetic diversity across African An. gambiae populations. We analyzed the complete datasets of 1142 individually sequenced mosquitoes through Microsoft Premonition's Bayesian mixture model based (BMM) metagenomics pipeline. All specimens were confirmed as either An. gambiae sensu stricto (s.s.) or An. coluzzii with a high degree of confidence ( > 98% identity to reference). Homo sapiens DNA was identified in all specimens indicating contamination may have occurred either at the time of specimen collection, preparation and/or sequencing. We found evidence of vertebrate hosts in 162 specimens. 59 specimens contained validated Plasmodium falciparum reads. Human hepatitis B and primate erythroparvovirus-1 viral sequences were identified in fifteen and three mosquito specimens, respectively. 478 of the 1,142 specimens were found to contain bacterial reads and bacteriophage-related contigs were detected in 27 specimens. This analysis demonstrates the capacity of metagenomic approaches to elucidate important vector-host-pathogen interactions of epidemiological significance.

Metagenomic surveillance uncovers diverse and novel viral taxa in febrile patients from Nigeria.

Effective infectious disease surveillance in high-risk regions is critical for clinical care and pandemic preemption; however, few clinical diagnostics are available for the wide range of potential human pathogens. Here, we conduct unbiased metagenomic sequencing of 593 samples from febrile Nigerian patients collected in three settings: i) population-level surveillance of individuals presenting with symptoms consistent with Lassa Fever (LF); ii) real-time investigations of outbreaks with suspected infectious etiologies; and iii) undiagnosed clinically challenging cases. We identify 13 distinct viruses, including the second and third documented cases of human blood-associated dicistrovirus, and a highly divergent, unclassified dicistrovirus that we name human blood-associated dicistrovirus 2. We show that pegivirus C is a common co-infection in individuals with LF and is associated with lower Lassa viral loads and favorable outcomes. We help uncover the causes of three outbreaks as yellow fever virus, monkeypox virus, and a noninfectious cause, the latter ultimately determined to be pesticide poisoning. We demonstrate that a local, Nigerian-driven metagenomics response to complex public health scenarios generates accurate, real-time differential diagnoses, yielding insights that inform policy.

The Year in Graduate Medical Education: Selected Highlights From 2021.

This special article is the first in a planned annual series for the Journal of Cardiothoracic and Vascular Anesthesia that will highlight significant literature from the world of graduate medical education (GME) that was published over the past year. The major themes selected for this inaugural review are the educational value of simulation and training workshops, the expanding role of social media and other information technologies in GME and recruitment, the state of residency and fellowship training before the COVID-19 pandemic, and the inevitable effects COVID-19 has had on graduate medical education. The authors would like to thank the editorial board for allowing us to shine a light on a small subset of the writing and research produced in this field, so that educators may understand how best to educate and train the next generation of anesthesiologists.

Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review.

BACKGROUND: As the adoption of artificial intelligence (AI) in health care increases, it will become increasingly crucial to involve health care professionals (HCPs) in developing, validating, and implementing AI-enabled technologies. However, because of a lack of AI literacy, most HCPs are not adequately prepared for this revolution. This is a significant barrier to adopting and implementing AI that will affect patients. In addition, the limited existing AI education programs face barriers to development and implementation at various levels of medical education. OBJECTIVE: With a view to informing future AI education programs for HCPs, this scoping review aims to provide an overview of the types of current or past AI education programs that pertains to the programs' curricular content, modes of delivery, critical implementation factors for education delivery, and outcomes used to assess the programs' effectiveness. METHODS: After the creation of a search strategy and keyword searches, a 2-stage screening process was conducted by 2 independent reviewers to determine study eligibility. When consensus was not reached, the conflict was resolved by consulting a third reviewer. This process consisted of a title and abstract scan and a full-text review. The articles were included if they discussed an actual training program or educational intervention, or a potential training program or educational intervention and the desired content to be covered, focused on AI, and were designed or intended for HCPs (at any stage of their career). RESULTS: Of the 10,094 unique citations scanned, 41 (0.41%) studies relevant to our eligibility criteria were identified. Among the 41 included studies, 10 (24%) described 13 unique programs and 31 (76%) discussed recommended curricular content. The curricular content of the unique programs ranged from AI use, AI interpretation, and cultivating skills to explain results derived from AI algorithms. The curricular topics were categorized into three main domains: cognitive, psychomotor, and affective. CONCLUSIONS: This review provides an overview of the current landscape of AI in medical education and highlights the skills and competencies required by HCPs to effectively use AI in enhancing the quality of care and optimizing patient outcomes. Future education efforts should focus on the development of regulatory strategies, a multidisciplinary approach to curriculum redesign, a competency-based curriculum, and patient-clinician interaction.

Accelerating the Appropriate Adoption of Artificial Intelligence in Health Care: Protocol for a Multistepped Approach.

BACKGROUND: Significant investments and advances in health care technologies and practices have created a need for digital and data-literate health care providers. Artificial intelligence (AI) algorithms transform the analysis, diagnosis, and treatment of medical conditions. Complex and massive data sets are informing significant health care decisions and clinical practices. The ability to read, manage, and interpret large data sets to provide data-driven care and to protect patient privacy are increasingly critical skills for today's health care providers. OBJECTIVE: The aim of this study is to accelerate the appropriate adoption of data-driven and AI-enhanced care by focusing on the mindsets, skillsets, and toolsets of point-of-care health providers and their leaders in the health system. METHODS: To accelerate the adoption of AI and the need for organizational change at a national level, our multistepped approach includes creating awareness and capacity building, learning through innovation and adoption, developing appropriate and strategic partnerships, and building effective knowledge exchange initiatives. Education interventions designed to adapt knowledge to the local context and address any challenges to knowledge use include engagement activities to increase awareness, educational curricula for health care providers and leaders, and the development of a coaching and practice-based innovation hub. Framed by the Knowledge-to-Action framework, we are currently in the knowledge creation stage to inform the curricula for each deliverable. An environmental scan and scoping review were conducted to understand the current state of AI education programs as reported in the academic literature. RESULTS: The environmental scan identified 24 AI-accredited programs specific to health providers, of which 11 were from the United States, 6 from Canada, 4 from the United Kingdom, and 3 from Asian countries. The most common curriculum topics across the environmental scan and scoping review included AI fundamentals, applications of AI, applied machine learning in health care, ethics, data science, and challenges to and opportunities for using AI. CONCLUSIONS: Technologies are advancing more rapidly than organizations, and professionals can adopt and adapt to them. To help shape AI practices, health care providers must have the skills and abilities to initiate change and shape the future of their discipline and practices for advancing high-quality care within the digital ecosystem. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/30940.

First lung and kidney multi-organ transplant following COVID-19 Infection.

As the world responds to the global crisis of the COVID-19 pandemic an increasing number of patients are experiencing increased morbidity as a result of multi-organ involvement. Of these, a small proportion will progress to end-stage lung disease, become dialysis dependent, or both. Herein, we describe the first reported case of a successful combined lung and kidney transplantation in a patient with COVID-19. Lung transplantation, isolated or combined with other organs, is feasible and should be considered for select patients impacted by this deadly disease.

Stability and detection of nucleic acid from viruses and hosts in controlled mosquito blood feeds.

Monitoring the presence and spread of pathogens in the environment is of critical importance. Rapid detection of infectious disease outbreaks and prediction of their spread can facilitate early responses of health agencies and reduce the severity of outbreaks. Current sampling methods are sorely limited by available personnel and throughput. For instance, xenosurveillance utilizes captured arthropod vectors, such as mosquitoes, as sampling tools to access blood from a wide variety of vertebrate hosts. Next generation sequencing (NGS) of nucleic acid from individual blooded mosquitoes can be used to identify mosquito and host species, and microorganisms including pathogens circulating within either host. However, there are practical challenges to collecting and processing mosquitoes for xenosurveillance, such as the rapid metabolization or decay of microorganisms within the mosquito midgut. This particularly affects pathogens that do not replicate in mosquitoes, preventing their detection by NGS or other methods. Accordingly, we performed a series of experiments to establish the windows of detection for DNA or RNA from human blood and/or viruses present in mosquito blood meals. Our results will contribute to the development of xenosurveillance techniques with respect to optimal timing of sample collection and NGS processing and will also aid trap design by demonstrating the stabilizing effect of temperature control on viral genome recovery from blood-fed mosquitoes.

Case Report of an Awake Craniotomy in a Patient With Eisenmenger Syndrome.

We present a detailed report of an awake craniotomy for recurrent third ventricular colloid cyst in a patient with severe pulmonary arterial hypertension in the setting of Eisenmenger syndrome, performed 6 weeks after we managed the same patient for a more conservative procedure. This patient has a high risk of perioperative mortality and may be particularly susceptible to perioperative hemodynamic changes or fluid shifts. The risks of general anesthesia induction and emergence must be balanced against the risks inherent in an awake craniotomy on a per case basis.

Draft Genome Sequence of a Novel Rhabdovirus Isolated from Deinocerites Mosquitoes.

We present a draft genome of a novel rhabdovirus, called Grenada mosquito rhabdovirus 1 (GMRV1), with homology to Wuhan mosquito virus 9 (WMV9) (NCBI reference sequence NC_031303), isolated from Deinocerites mosquitoes. The genome has a length of 14,420 nucleotides and encodes five open reading frames.

An improved method for detecting torpor entrance and arousal in a mammalian hibernator using heart rate data.

We used electrocardiogram (ECG) telemeters to measure the heart rate of hibernating Ictidomys tridecemlineatus (thirteen-lined ground squirrel). An increase in heart rate from 2.2 to 5 beats min-1 accurately identified arousal from torpor before any change in body temperature was detected. Variability in raw heart rate data was significantly reduced by a forward-backward Butterworth low-pass filter, allowing for discrete differential analysis. A decrease in filtered heart rate to 70% of maximum values in interbout euthermia (from approximately 312 to 235 beats min-1) accurately detected entrance into torpor bouts. At this point, body temperature had fallen from 36.1°C to only 34.7°C, much higher than the 30°C typically used to identify entrance. Using these heart rate criteria allowed advanced detection of entrance and arousal (detected 51.9 and 76 min earlier, respectively), compared with traditional body temperature criteria. This method will improve our ability to detect biochemical and molecular markers underlying these transition periods, during which many physiological changes occur.

Logic programming to predict cell fate patterns and retrodict genotypes in organogenesis.

Caenorhabditis elegans vulval development is a paradigm system for understanding cell differentiation in the process of organogenesis. Through temporal and spatial controls, the fate pattern of six cells is determined by the competition of the LET-23 and the Notch signalling pathways. Modelling cell fate determination in vulval development using state-based models, coupled with formal analysis techniques, has been established as a powerful approach in predicting the outcome of combinations of mutations. However, computing the outcomes of complex and highly concurrent models can become prohibitive. Here, we show how logic programs derived from state machines describing the differentiation of C. elegans vulval precursor cells can increase the speed of prediction by four orders of magnitude relative to previous approaches. Moreover, this increase in speed allows us to infer, or 'retrodict', compatible genomes from cell fate patterns. We exploit this technique to predict highly variable cell fate patterns resulting from dig-1 reduced-function mutations and let-23 mosaics. In addition to the new insights offered, we propose our technique as a platform for aiding the design and analysis of experimental data.

A method of rapid robust respiratory synchronization for MRI.

Respiratory motion degrades MRI exams. Adequate detection of respiratory motion with pneumatic respiratory belts in small children is challenging and time-consuming.

The effects of dexmedetomidine on cardiac electrophysiology in children.

BACKGROUND: Dexmedetomidine (DEX) is an alpha2-adrenergic agonist that is approved by the Food and Drug Administration for short-term (<24 h) sedation in adults. It is not approved for use in children. Nevertheless, the use of DEX for sedation and anesthesia in infants and children appears to be increasing. There are some concerns regarding the hemodynamic effects of the drug, including bradycardia, hypertension, and hypotension. No data regarding the effects of DEX on the cardiac conduction system are available. We therefore aimed to characterize the effects of DEX on cardiac conduction in pediatric patients. METHODS: Twelve children between the ages of 5 and 17 yr undergoing electrophysiology study and ablation of supraventricular accessory pathways had hemodynamic and cardiac electrophysiologic variables measured before and during administration of DEX (1 microg/kg IV over 10 min followed by a 10-min continuous infusion of 0.7 microg x kg(-1) x h(-1)). RESULTS: Heart rate decreased while arterial blood pressure increased significantly after DEX administration. Sinus node function was significantly affected, as evidenced by an increase in sinus cycle length and sinus node recovery time. Atrioventricular nodal function was also depressed, as evidenced by Wenckeback cycle length prolongation and prolongation of PR interval. CONCLUSION: DEX significantly depressed sinus and atrioventricular nodal function in pediatric patients. Heart rate decreased and arterial blood pressure increased during administration of DEX. The use of DEX may not be desirable during electrophysiology study and may be associated with adverse effects in patients at risk for bradycardia or atrioventricular nodal block.