The PPARα-PGC-1α Axis Controls Cardiac Energy Metabolism in Healthy and Diseased Myocardium

The mammalian myocardium is an omnivorous organ that relies on multiple substrates in order to fulfill its tremendous energy demands. Cardiac energy metabolism preference is regulated at several critical points, including at the level of gene transcription. Emerging evidence indicates that the nuclear receptor PPARα and its cardiac-enriched coactivator protein, PGC-1α, play important roles in the transcriptional control of myocardial energy metabolism. The PPARα-PGC-1α complex controls the expression of genes encoding enzymes involved in cardiac fatty acid and glucose metabolism as well as mitochondrial biogenesis. Also, evidence has emerged that the activity of the PPARα-PGC-1α complex is perturbed in several pathophysiologic conditions and that altered activity of this pathway may play a role in cardiomyopathic remodeling. In this review, we detail the current understanding of the effects of the PPARα-PGC-1α axis in regulating mitochondrial energy metabolism and cardiac function in response to physiologic and pathophysiologic stimuli

Time-bin to Polarization Conversion of Ultrafast Photonic Qubits

The encoding of quantum information in photonic time-bin qubits is apt for long distance quantum communication schemes. In practice, due to technical constraints such as detector response time, or the speed with which co-polarized time-bins can be switched, other encodings, e.g. polarization, are often preferred for operations like state detection. Here, we present the conversion of qubits between polarization and time-bin encodings using a method that is based on an ultrafast optical Kerr shutter and attain efficiencies of 97% and an average fidelity of 0.827+/-0.003 with shutter speeds near 1 ps. Our demonstration delineates an essential requirement for the development of hybrid and high-rate optical quantum networks

Risk factors associated with physician trainee concern over missed educational opportunities during the COVID-19 pandemic

BACKGROUND: The COVID-19 pandemic resulted in a transformation of clinical care practices to protect both patients and providers. These changes led to a decrease in patient volume, impacting physician trainee education due to lost clinical and didactic opportunities. We measured the prevalence of trainee concern over missed educational opportunities and investigated the risk factors leading to such concerns. METHODS: All residents and fellows at a large academic medical center were invited to participate in a web-based survey in May of 2020. Participants responded to questions regarding demographic characteristics, specialty, primary assigned responsibility during the previous 2 weeks (clinical, education, or research), perceived concern over missed educational opportunities, and burnout. Multivariable logistic regression was used to assess the relationship between missed educational opportunities and the measured variables. RESULTS: 22% (301 of 1375) of the trainees completed the survey. 47% of the participants were concerned about missed educational opportunities. Trainees assigned to education at home had 2.85 [95%CI 1.33-6.45] greater odds of being concerned over missed educational opportunities as compared with trainees performing clinical work. Trainees performing research were not similarly affected [aOR = 0.96, 95%CI (0.47-1.93)]. Trainees in pathology or radiology had 2.51 [95%CI 1.16-5.68] greater odds of concern for missed educational opportunities as compared with medicine. Trainees with greater concern over missed opportunities were more likely to be experiencing burnout (p = 0.038). CONCLUSIONS: Trainees in radiology or pathology and those assigned to education at home were more likely to be concerned about their missed educational opportunities. Residency programs should consider providing trainees with research or at home clinical opportunities as an alternative to self-study should future need for reduced clinical hours arise

Two Devices for Removing Sludge From Bioreactor Wastewater

Two devices a magnetic separator and a special filter denoted a self-regenerating separator (SRS) have been developed for separating sludge from the stream of wastewater from a bioreactor. These devices were originally intended for use in microgravity, but have also been demonstrated to function in normal Earth gravity. The magnetic separator (see Figure 1) includes a thin-walled nonmagnetic, stainless-steel cylindrical drum that rotates within a cylindrical housing. The wastewater enters the separator through a recirculation inlet, and about 80 percent of the wastewater flow leaves through a recirculation outlet. Inside the drum, a magnet holder positions strong permanent magnets stationary and, except near a recirculation outlet, close to the inner drum surface. To enable magnetic separation, magnetite (a ferromagnetic and magnetically soft iron oxide) powder is mixed into the bioreactor wastewater. The magnetite becomes incorporated into the sludge by condensation, onto the powder particles, of microbe flocks that constitute the sludge. As a result, the magnets inside the drum magnetically attract the sludge onto the outer surface of the drum

Exposure to COVID-19 patients increases physician trainee stress and burnout

The coronavirus disease 2019 (COVID-19) pandemic has put considerable physical and emotional strain on frontline healthcare workers. Among frontline healthcare workers, physician trainees represent a unique group-functioning simultaneously as both learners and caregivers and experiencing considerable challenges during the pandemic. However, we have a limited understanding regarding the emotional effects and vulnerability experienced by trainees during the pandemic. We investigated the effects of trainee exposure to patients being tested for COVID-19 on their depression, anxiety, stress, burnout and professional fulfillment. All physician trainees at an academic medical center (n = 1375) were invited to participate in an online survey. We compared the measures of depression, anxiety, stress, burnout and professional fulfillment among trainees who were exposed to patients being tested for COVID-19 and those that were not, using univariable and multivariable models. We also evaluated perceived life stressors such as childcare, home schooling, personal finances and work-family balance among both groups. 393 trainees completed the survey (29% response rate). Compared to the non-exposed group, the exposed group had a higher prevalence of stress (29.4% vs. 18.9%), and burnout (46.3% vs. 33.7%). The exposed group also experienced moderate to extremely high perceived stress regarding childcare and had a lower work-family balance. Multivariable models indicated that trainees who were exposed to COVID-19 patients reported significantly higher stress (10.96 [95% CI, 9.65 to 12.46] vs 8.44 [95% CI, 7.3 to 9.76]; P = 0.043) and were more likely to be burned out (1.31 [95% CI, 1.21 to1.41] vs 1.07 [95% CI, 0.96 to 1.19]; P = 0.002]. We also found that female trainees were more likely to be stressed (P = 0.043); while unmarried trainees were more likely to be depressed (P = 0.009), and marginally more likely to have anxiety (P = 0.051). To address these challenges, wellness programs should focus on sustaining current programs, develop new and targeted mental health resources that are widely accessible and devise strategies for creating awareness regarding these resources

Work-related and personal factors associated with mental well-being during the COVID-19 response: Survey of health care and other workers

BACKGROUND: The response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has created an unprecedented disruption in work conditions. This study describes the mental health and well-being of workers both with and without clinical exposure to patients with coronavirus disease (COVID-19). OBJECTIVE: The aim of this study is to measure the prevalence of stress, anxiety, depression, work exhaustion, burnout, and decreased well-being among faculty and staff at a university and academic medical center during the SARS-CoV-2 pandemic and describe work-related and personal factors associated with their mental health and well-being. METHODS: All faculty, staff, and postdoctoral fellows of a university, including its medical school, were invited in April 2020 to complete an online questionnaire measuring stress, anxiety, depression, work exhaustion, burnout, and decreased well-being. We examined associations between these outcomes and factors including work in high-risk clinical settings and family/home stressors. RESULTS: There were 5550 respondents (overall response rate of 34.3%). Overall, 34% of faculty and 14% of staff (n=915) were providing clinical care, while 61% of faculty and 77% of staff were working from home. Among all workers, anxiety (prevalence ratio 1.37, 95% CI 1.09-1.73), depression (prevalence ratio 1.28, 95% CI 1.03-1.59), and high work exhaustion (prevalence ratio 1.24, 95% CI 1.13-1.36) were independently associated with community or clinical exposure to COVID-19. Poor family-supportive behaviors by supervisors were also associated with these outcomes (prevalence ratio 1.40, 95% CI 1.21-1.62; prevalence ratio 1.69, 95% CI 1.48-1.92; and prevalence ratio 1.54, 95% CI 1.44-1.64, respectively). Age \u3c40 years and a greater number of family/home stressors were also associated with these poorer outcomes. Among the subset of clinicians, caring for patients with COVID-19 and working in high-risk clinical settings were additional risk factors. CONCLUSIONS: Our findings suggest that the pandemic has had negative effects on the mental health and well-being of both clinical and nonclinical employees. Mitigating exposure to COVID-19 and increasing supervisor support are modifiable risk factors that may protect mental health and well-being for all workers

The secret hidden in dust:Assessing the potential to use biological and chemical properties of the airborne fraction of soil for provenance assignment and forensic casework

The airborne fraction of soil (dust) is both ubiquitous in nature and contains localised biological and chemical signatures, making it a potential medium for forensic intelligence. Metabarcoding of dust can yield biological communities unique to the site of interest, similarly, geochemical analyses can uncover elements and minerals within dust that can be matched to a geographic location. Combining these analyses presents multiple lines of evidence as to the origin of dust collected from items of interest. In this work, we investigated whether bacterial and fungal communities in dust change through time and whether they are comparable to soil samples of the same site. We integrated dust metabarcoding into a framework amenable to forensic casework, (i.e., using calibrated log-likelihood ratios) to predict the origin of dust samples using models constructed from both dust samples and soil samples from the same site. Furthermore, we tested whether both metabarcoding and geochemical/mineralogical analyses could be conducted on a single swabbed sample, for situations where sampling is limited. We found both analyses could generate results from a single swabbed sample and found biological and chemical signatures unique to sites. However, we did find significant variation within sites, where this did not always correlate with time but was a random effect of sampling. This variation within sites was not greater than between sites and so did not influence site discrimination. When modelling bacterial and fungal diversity using calibrated log-likelihood ratios, we found samples were correctly predicted using dust 67% and 56% of the time and using soil 56% and 22% of the time for bacteria and fungi communities respectively. Incorrect predictions were related to within site variability, highlighting limitations to assigning dust provenance using metabarcoding of soil.</p

Dynamic instability of the major urinary protein gene family revealed by genomic and phenotypic comparisons between C57 and 129 strain mice

Targeted sequencing, manual genome annotation, phylogenetic analysis and mass spectrometry were used to characterise major urinary proteins (MUPs) and the Mup clusters of two strains of inbred mice