Gene expression and chromatin conformation of microglia in virally suppressed people with HIV.

The presence of HIV in sequestered reservoirs is a central impediment to a functional cure, allowing HIV to persist despite life-long antiretroviral therapy (ART), and driving a variety of comorbid conditions. Our understanding of the latent HIV reservoir in the central nervous system is incomplete, because of difficulties in accessing human central nervous system tissues. Microglia contribute to HIV reservoirs, but the molecular phenotype of HIV-infected microglia is poorly understood. We leveraged the unique "Last Gift" rapid autopsy program, in which people with HIV are closely followed until days or even hours before death. Microglial populations were heterogeneous regarding their gene expression profiles but showed similar chromatin accessibility landscapes. Despite ART, we detected occasional microglia containing cell-associated HIV RNA and HIV DNA integrated into open regions of the host's genome (∼0.005%). Microglia with detectable HIV RNA showed an inflammatory phenotype. These results demonstrate a distinct myeloid cell reservoir in the brains of people with HIV despite suppressive ART. Strategies for curing HIV and neurocognitive impairment will need to consider the myeloid compartment to be successful.

Title evaluation of FluSight influenza forecasting in the 2021-22 and 2022-23 seasons with a new target laboratory-confirmed influenza hospitalizations.

Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021-22 and 2022-23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021-22 and 12 out of 18 models in 2022-23. Averaging across all forecast targets, the FluSight ensemble is the 2nd most accurate model measured by WIS in 2021-22 and the 5th most accurate in the 2022-23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

HIV vaccines induce CD8+ T cells with low antigen receptor sensitivity.

Current HIV vaccines designed to stimulate CD8+ T cells have failed to induce immunologic control upon infection. The functions of vaccine-induced HIV-specific CD8+ T cells were investigated here in detail. Cytotoxic capacity was significantly lower than in HIV controllers and was not a consequence of low frequency or unaccumulated functional cytotoxic proteins. Low cytotoxic capacity was attributable to impaired degranulation in response to the low antigen levels present on HIV-infected targets. The vaccine-induced T cell receptor (TCR) repertoire was polyclonal and transduction of these TCRs conferred the same reduced functions. These results define a mechanism accounting for poor antiviral activity induced by these vaccines and suggest that an effective CD8+ T cell response may require a vaccination strategy that drives further TCR clonal selection.

An in vivo neuroimmune organoid model to study human microglia phenotypes.

Microglia are specialized brain-resident macrophages that play crucial roles in brain development, homeostasis, and disease. However, until now, the ability to model interactions between the human brain environment and microglia has been severely limited. To overcome these limitations, we developed an in vivo xenotransplantation approach that allows us to study functionally mature human microglia (hMGs) that operate within a physiologically relevant, vascularized immunocompetent human brain organoid (iHBO) model. Our data show that organoid-resident hMGs gain human-specific transcriptomic signatures that closely resemble their in vivo counterparts. In vivo two-photon imaging reveals that hMGs actively engage in surveilling the human brain environment, react to local injuries, and respond to systemic inflammatory cues. Finally, we demonstrate that the transplanted iHBOs developed here offer the unprecedented opportunity to study functional human microglia phenotypes in health and disease and provide experimental evidence for a brain-environment-induced immune response in a patient-specific model of autism with macrocephaly.

Mach 18 flow velocimetry with 100-kHz KTV and PLEET in AEDC Tunnel 9.

Krypton Tagging Velocimetry (KTV) and Picosecond Laser Electronic Excitation Tagging (PLEET) velocimetry at a 100-kHz rate were demonstrated in Mach 18 flow conditions at the Arnold Engineering Development Center (AEDC) Tunnel 9 employing a burst-mode laser system and a custom optical parametric oscillator (OPO). The measured freestream flow velocities from both KTV and PLEET agreed well with the theoretical calculation. The increase in repetition rate provides better capability to perform time-resolved velocimetry measurements in hypersonic flow environments.

Rate of Inpatient Hypoglycemia Following a 1:1 Dose Interchange Between Concentrated Insulin Glargine to Insulin Detemir.

BACKGROUND: Insulin remains a mainstay of treating hyperglycemia in an acute setting. Insulin glargine 300 units/mL (Toujeo, iGlar300) has a different pharmacokinetic profile than 100 units/mL basal insulins, such as insulin detemir (iDet100) and iGlar100. While conversion from iGlar300 to iGlar100 requires a 20% dose decrease, there is currently no recommended interchange from iGlar300 to iDet100. OBJECTIVE: Compare the incidence of hypoglycemia in patients who received a 1:1 unit interchange from home iGlar300 or iGlar100 to iDet100 while admitted. METHODS: A retrospective study was conducted to evaluate adults within a multi-site network admitted between May and December 2019. Patients were included if they received at least one dose of iDet100 following interchange from home iGlar300 or iGlar100. The primary endpoint was the incidence of hypoglycemic events following a 1:1 interchange of iGlar300 vs. iGlar100 to inpatient iDet100. Secondary outcomes include overall hypoglycemic events, time to hypoglycemia, and doses given before hypoglycemia. RESULTS: Of 615 patients, 394 received a 1:1 unit interchange to iDet100 (52 from iGlar300 and 342 from iGlar100). Incidence of hypoglycemic events was significantly higher in those with a 1:1 interchange from iGlar300 versus iGlar100 (36.5% vs. 18.7%, p = 0.007). Significant differences were observed in overall hypoglycemic events, time to hypoglycemia, and number of doses given before hypoglycemic event. CONCLUSION AND RELEVANCE: A 1:1 unit interchange from iGlar300 to iDet100 led to a higher incidence of hypoglycemic events compared to those interchanged from iGlar100. Dose reduction should be considered when transitioning from home iGlar300 to iDet100 in the inpatient setting.

Evaluation of FluSight influenza forecasting in the 2021-22 and 2022-23 seasons with a new target laboratory-confirmed influenza hospitalizations.

Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. Forecasting teams were asked to provide national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one through four weeks ahead for the 2021-22 and 2022-23 influenza seasons. Across both seasons, 26 teams submitted forecasts, with the submitting teams varying between seasons. Forecast skill was evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperformed the baseline model across forecast weeks and locations in 2021-22 and 12 out of 18 models in 2022-23. Averaging across all forecast targets, the FluSight ensemble was the 2nd most accurate model measured by WIS in 2021-22 and the 5th most accurate in the 2022-23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degraded over longer forecast horizons and during periods of rapid change. Current influenza forecasting efforts help inform situational awareness, but research is needed to address limitations, including decreased performance during periods of changing epidemic dynamics.

Nonadiabatic transition paths from quantum jump trajectories.

We present a means of studying rare reactive pathways in open quantum systems using transition path theory and ensembles of quantum jump trajectories. This approach allows for the elucidation of reactive paths for dissipative, nonadiabatic dynamics when the system is embedded in a Markovian environment. We detail the dominant pathways and rates of thermally activated processes and the relaxation pathways and photoyields following vertical excitation in a minimal model of a conical intersection. We find that the geometry of the conical intersection affects the electronic character of the transition state as defined through a generalization of a committor function for a thermal barrier crossing event. Similarly, the geometry changes the mechanism of relaxation following a vertical excitation. Relaxation in models resulting from small diabatic coupling proceeds through pathways dominated by pure dephasing, while those with large diabatic coupling proceed through pathways limited by dissipation. The perspective introduced here for the nonadiabatic dynamics of open quantum systems generalizes classical notions of reactive paths to fundamentally quantum mechanical processes.

Advancing diversity, equity, and inclusion within clinical and translational science training programs: A qualitative content analysis of the training breakout session at the national CTSA program meeting.

Background: Diversity, equity, and inclusion (DEI) in clinical and translational science (CTS) are paramount to driving innovation and increasing health equity. One important area for improving diversity is among trainees in CTS programs. This paper reports on findings from a special session at the November 2020 Clinical and Translational Science Award (CTSA) national program meeting that focused on advancing diversity and inclusion within CTS training programs. Methods: Using qualitative content analysis, we identified approaches brought forth to increase DEI in KL2 career development and other training programs aimed at early-stage CTS investigators, beyond the six strategies put forth to guide the breakout session (prioritizing representation, building partnerships, making it personal, designing program structure, improving through feedback, and winning endorsement). We used an inductive qualitative content analysis approach to identify themes from a transcript of the panel of KL2 program leaders centered on DEI in training programs. Results: We identified four themes for advancing DEI within CTS training programs: 1) institutional buy-in; 2) proactive recruitment efforts; 3) an equitable application process; and 4) high-quality, diverse mentorship. Conclusion: Implementing these strategies in CTS and other training programs will be an important step for advancing DEI. However, processes need to be established to evaluate the implementation and effectiveness of these strategies through continuous quality improvement, a key component of the CTSA program. Training programs within the CTSA are well-positioned to be leaders in this critical effort to increase the diversity of the scientific workforce.

Somatic mosaicism reveals clonal distributions of neocortical development.

The structure of the human neocortex underlies species-specific traits and reflects intricate developmental programs. Here we sought to reconstruct processes that occur during early development by sampling adult human tissues. We analysed neocortical clones in a post-mortem human brain through a comprehensive assessment of brain somatic mosaicism, acting as neutral lineage recorders1,2. We combined the sampling of 25 distinct anatomic locations with deep whole-genome sequencing in a neurotypical deceased individual and confirmed results with 5 samples collected from each of three additional donors. We identified 259 bona fide mosaic variants from the index case, then deconvolved distinct geographical, cell-type and clade organizations across the brain and other organs. We found that clones derived after the accumulation of 90-200 progenitors in the cerebral cortex tended to respect the midline axis, well before the anterior-posterior or ventral-dorsal axes, representing a secondary hierarchy following the overall patterning of forebrain and hindbrain domains. Clones across neocortically derived cells were consistent with a dual origin from both dorsal and ventral cellular populations, similar to rodents, whereas the microglia lineage appeared distinct from other resident brain cells. Our data provide a comprehensive analysis of brain somatic mosaicism across the neocortex and demonstrate cellular origins and progenitor distribution patterns within the human brain.

Monosodium urate crystals regulate a unique JNK-dependent macrophage metabolic and inflammatory response.

Monosodium urate crystals (MSUc) induce inflammation in vivo without prior priming, raising the possibility of an initial cell-autonomous phase. Here, using genome-wide transcriptomic analysis and biochemical assays, we demonstrate that MSUc alone induce a metabolic-inflammatory transcriptional program in non-primed human and murine macrophages that is markedly distinct to that induced by LPS. Genes uniquely upregulated in response to MSUc belong to lipid and amino acid metabolism, glycolysis, and SLC transporters. This upregulation leads to a metabolic rewiring in sera from individuals and mice with acute gouty arthritis. Mechanistically, the initiating inflammatory-metabolic changes in acute gout flares are regulated through a persistent expression and increased binding of JUN to the promoter of target genes through JNK signaling-but not P38-in a process that is different than after LPS stimulation and independent of inflammasome activation. Finally, pharmacological JNK inhibition limits MSUc-induced inflammation in animal models of acute gouty inflammation.

Impact of a pharmacist-inclusive post-discharge clinic on outcomes in heart failure patients with reduced ejection fraction: Rates of hospital readmission, emergency department visits, or death.

INTRODUCTION: Heart failure hospitalization is a hallmark of disease progression associated with increased morbidity and mortality. Benefits of multidisciplinary clinics have been established in the care of heart failure patients and can be particularly impactful post-hospital discharge. OBJECTIVE: This study aimed to investigate the impact of a clinical pharmacist-integrated model of care within a Heart Failure Bridge Clinic (HFBC) at a large tertiary care referral center. METHODS: In this single-center retrospective study, patients with left ventricular ejection fraction (LVEF) ≤40% discharged from Mission Hospital (Asheville, North Carolina) between August 2018 and July 2019 were screened. Patients in the HFBC arm had a clinic visit inclusive of a clinical pharmacist within 30 days of hospital discharge and were compared with a control group of patients with a usual care provider clinic visit. The HFBC provided clinical assessment, detailed heart failure education, and medication reconciliation and adjustment with an emphasis on optimization of Guideline Directed Medical Therapy (GDMT). Patients were followed for 90 days for the primary end point of hospitalization, emergency department (ED) visit, or death. RESULTS: A total of 1463 patients (HFBC, n = 307; control, n = 1156) comprised our final cohort. After accounting for baseline variables, 90-day cumulative probability of hospitalization, ED visit, or death favored HFBC patients (26% vs 32%, P = .0275). Comprehensive review of medications prior to and after HFBC appointment demonstrated significant alterations to therapies (30% GDMT addition, 27% GDMT titration, 7.2% discontinuation of medications associated with worsening heart failure, and 28% loop diuretic adjustment). CONCLUSION: Clinical pharmacist-integrated HFBC allows for focused medication review and optimization and is associated with a 19% relative risk reduction in hospitalization, ED visit, or death at 90 days.

Can auxiliary indicators improve COVID-19 forecasting and hotspot prediction?

Short-term forecasts of traditional streams from public health reporting (such as cases, hospitalizations, and deaths) are a key input to public health decision-making during a pandemic. Since early 2020, our research group has worked with data partners to collect, curate, and make publicly available numerous real-time COVID-19 indicators, providing multiple views of pandemic activity in the United States. This paper studies the utility of five such indicators-derived from deidentified medical insurance claims, self-reported symptoms from online surveys, and COVID-related Google search activity-from a forecasting perspective. For each indicator, we ask whether its inclusion in an autoregressive (AR) model leads to improved predictive accuracy relative to the same model excluding it. Such an AR model, without external features, is already competitive with many top COVID-19 forecasting models in use today. Our analysis reveals that 1) inclusion of each of these five indicators improves on the overall predictive accuracy of the AR model; 2) predictive gains are in general most pronounced during times in which COVID cases are trending in "flat" or "down" directions; and 3) one indicator, based on Google searches, seems to be particularly helpful during "up" trends.

An open repository of real-time COVID-19 indicators.

The COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt to fill this need: Operational since April 2020, it provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID-19 activity, such as signals extracted from deidentified medical claims data, massive online surveys, cell phone mobility data, and internet search trends. These are available at a fine geographic resolution (mostly at the county level) and are updated daily. The COVIDcast API also tracks all revisions to historical data, allowing modelers to account for the frequent revisions and backfill that are common for many public health data sources. All of the data are available in a common format through the API and accompanying R and Python software packages. This paper describes the data sources and signals, and provides examples demonstrating that the auxiliary signals in the COVIDcast API present information relevant to tracking COVID activity, augmenting traditional public health reporting and empowering research and decision-making.

Vibronic coupling in energy transfer dynamics and two-dimensional electronic-vibrational spectra.

We introduce a heterodimer model in which multiple mechanisms of vibronic coupling and their impact on energy transfer can be explicitly studied. We consider vibronic coupling that arises through either Franck-Condon activity in which each site in the heterodimer has a local electron-phonon coupling or Herzberg-Teller activity in which the transition dipole moment coupling the sites has an explicit vibrational mode-dependence. We have computed two-dimensional electronic-vibrational (2DEV) spectra for this model while varying the magnitude of these two effects and find that 2DEV spectra contain static and dynamic signatures of both types of vibronic coupling. Franck-Condon activity emerges through a change in the observed excitonic structure, while Herzberg-Teller activity is evident in the appearance of significant side-band transitions that mimic the lower-energy excitonic structure. A comparison of quantum beating patterns obtained from analysis of the simulated 2DEV spectra shows that this technique can report on the mechanism of energy transfer, elucidating a means of experimentally determining the role of specific vibronic coupling mechanisms in such processes.

An Open Repository of Real-Time COVID-19 Indicators

The COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt to fill this need: operational since April 2020, it provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID-19 activity, such as signals extracted from de-identified medical claims data, massive online surveys, cell phone mobility data, and internet search trends. These are available at a fine geographic resolution (mostly at the county level) and are updated daily. The COVIDcast API also tracks all revisions to historical data, allowing modelers to account for the frequent revisions and backfill that are common for many public health data sources. All of the data is available in a common format through the API and accompanying R and Python software packages. This paper describes the data sources and signals, and provides examples demonstrating that the auxiliary signals in the COVIDcast API present information relevant to tracking COVID activity, augmenting traditional public health reporting and empowering research and decision-making.

Can Auxiliary Indicators Improve COVID-19 Forecasting and Hotspot Prediction?

Short-term forecasts of traditional streams from public health reporting (such as cases, hospitalizations, and deaths) are a key input to public health decision-making during a pandemic. Since early 2020, our research group has worked with data partners to collect, curate, and make publicly available numerous real-time COVID-19 indicators, providing multiple views of pandemic activity in the U.S. This paper studies the utility of five such indicators--derived from de-identified medical insurance claims, self-reported symptoms from online surveys, and COVID-related Google search activity--from a forecasting perspective. For each indicator, we ask whether its inclusion in an autoregressive (AR) model leads to improved predictive accuracy relative to the same model excluding it. Such an AR model, without external features, is already competitive with many top COVID-19 forecasting models in use today. Our analysis reveals that (a) inclusion of each of these five indicators improves on the overall predictive accuracy of the AR model; (b) predictive gains are in general most pronounced during times in which COVID cases are trending in "flat" or "down" directions; (c) one indicator, based on Google searches, seems to be particularly helpful during "up" trends.

Kokumi taste perception is functional in a model carnivore, the domestic cat (Felis catus).

Kokumi taste is a well-accepted and characterised taste modality and is described as a sensation of enhancement of sweet, salty, and umami tastes. The Calcium Sensing Receptor (CaSR) has been designated as the putative kokumi taste receptor for humans, and a number of kokumi-active ligands of CaSR have been discovered recently with activity confirmed both in vivo and in vitro. Domestic cats (Felis catus) are obligate carnivores and accordingly, their diet is abundant in proteins, peptides, and amino acids. We hypothesised that CaSR is a key taste receptor for carnivores, due to its role in the detection of different peptides and amino acids in other species. Using in silico, in vitro and in vivo approaches, here we compare human CaSR to that of a model carnivore, the domestic cat. We found broad similarities in ligand specificity, but differences in taste sensitivity between the two species. Indeed our in vivo data shows that cats are sensitive to CaCl2 as a kokumi compound, but don't show this same activity with Glutathione, whereas for humans the reverse is true. Collectively, our data suggest that kokumi is an important taste modality for carnivores that drives the palatability of meat-derived compounds such as amino acids and peptides, and that there are differences in the perception of kokumi taste between carnivores and omnivores.