Extended haplotype with rs41524547-G defines the ancestral origin of SCA10.

Spinocerebellar ataxia type 10 (SCA10) is a rare autosomal dominant ataxia caused by a large expansion of the (ATTCT)n repeat in ATXN10. SCA10 was described in Native American and Asian individuals which prompted a search for an expanded haplotype to confirm a common ancestral origin for the expansion event. All patients with SCA10 expansions in our cohort share a single haplotype defined at the 5'-end by the minor allele of rs41524547, located ~35 kb upstream of the SCA10 expansion. Intriguingly, rs41524547 is located within the miRNA gene, MIR4762, within its DROSHA cleavage site and just outside the seed sequence for mir4792-5p. The world-wide frequency of rs41524547-G is less than 5% and found almost exclusively in the Americas and East Asia-a geographic distribution that mirrors reported SCA10 cases. We identified rs41524547-G(+) DNA from the 1000 Genomes/International Genome Sample Resource and our own general population samples and identified SCA10 repeat expansions in up to 25% of these samples. The reduced penetrance of these SCA10 expansions may be explained by a young (pre-onset) age at sample collection, a small repeat size, purity of repeat units, or the disruption of miR4762-5p function. We conclude that rs41524547-G is the most robust at-risk SNP allele for SCA10, is useful for screening of SCA10 expansions in population genetics studies and provides the most compelling evidence to date for a single, prehistoric origin of SCA10 expansions sometime prior to or during the migration of individuals across the Bering Land Bridge into the Americas.

Preoperative hyponatremia and survival after left ventricular assist device implantation.

BACKGROUND: Hyponatremia is associated with adverse outcomes in heart failure and after cardiac surgery. We hypothesized that hyponatremia is associated with poorer short-term and longer term survival in patients after continuous-flow left ventricular assist device (CF-LVAD) placement. METHODS: We reviewed a single-center database of patients who received a CF-LVAD during 2012-2017. Sodium (Na) values obtained within 14 days before CF-LVAD insertion were averaged; patients (n = 332) were divided into hyponatremia (mean Na <135 mEq/L; n = 160; 48.2%) and normonatremia groups (mean Na 135-145 mEq/L; n = 172; 51.8%). Patients requiring preoperative dialysis or pump exchange were excluded. We compared outcomes between preoperative hyponatremia and normonatremia groups. RESULTS: The two groups' baseline characteristics were similar, although hyponatremia patients more often had preoperative mechanical circulatory support (44.4% vs. 31.4%, p = 0.002). Although hyponatremic and normonatremic patients did not differ in 30-day mortality (7.5% vs. 6.5%, p = 0.7), preoperative hyponatremia was associated with greater 5-year mortality (61% vs. 44%, p = 0.03). On binary logistic regression analysis, the strongest independent predictors of late mortality were hyponatremia (odds ratio [OR] 1.88, 95% CI [1.07-3.31], p = 0.02), older age (OR 1.03, 95% CI [1.01-1.05], p = 0.01), and elevated mean right atrial pressure/pulmonary capillary wedge pressure ratio (OR 4.69, 95% CI [1.76-12.47], p = 0.002). CONCLUSIONS: Hyponatremia was not associated with greater early mortality but was associated with poorer late survival. The optimal timing of LVAD implantation in relation to hyponatremia, and whether correcting hyponatremia perioperatively improves long-term survival, should be investigated.

Predictors of renal replacement therapy in patients with continuous flow left ventricular assist devices.

Renal replacement therapy (RRT) after continuous flow left ventricular assist device (CF-LVAD) implantation significantly affects patients' quality of life and survival. To identify preoperative prognostic markers in patients requiring RRT after CF-LVAD implantation, we retrospectively reviewed data from patients who underwent implantation of a CF-LVAD at our institution during 2012-2017. Patients who required preoperative RRT were excluded. Preoperative and operative characteristics, as well as survival and adverse events, were compared between 74 (22.2%) patients requiring any duration of postoperative RRT and 259 (77.8%) not requiring RRT. Patients requiring RRT experienced more postoperative complications than patients who did not, including respiratory failure necessitating tracheostomy (35.7% vs 2.5%, p < 0.001), reoperation for bleeding (34.3% vs 11.7%, p < 0.001), and right heart failure necessitating perioperative mechanical circulatory support (32.4% vs 6.9%, p < 0.001). Patients requiring postoperative RRT also had poorer survival at 30 days (74.7% vs 98.8%), 6 months (48.2% vs 95.1%), and 12 months (45.3% vs 90.2%) (p < 0.001). Significant predictors of RRT after CF-LVAD implantation included urine proteinuria (odds ratio [OR] 3.6, 95% confidence interval [CI] [1.7-7.6], p = 0.001), estimated glomerular filtration rate < 45 mL/min/1.73 m2 (OR 3.4, 95% CI [1.5-17.8], p = 0.004), and mean right atrial pressure to pulmonary capillary wedge pressure ratio ≥ 0.54 (OR 2.6, 95% CI [1.3-5.], p = 0.01). Of the 74 RRT patients, 11 (14.9%) recovered renal function before discharge, 36 (48.6%) still required RRT after discharge, and 27 (36.5%) died before discharge. We conclude that preoperative renal and right ventricular dysfunction significantly predict postoperative renal failure and mortality after CF-LVAD implantation.

Precuneus shares intrinsic functional architecture in humans and monkeys.

Evidence from macaque monkey tracing studies suggests connectivity-based subdivisions within the precuneus, offering predictions for similar subdivisions in the human. Here we present functional connectivity analyses of this region using resting-state functional MRI data collected from both humans and macaque monkeys. Three distinct patterns of functional connectivity were demonstrated within the precuneus of both species, with each subdivision suggesting a discrete functional role: (i) the anterior precuneus, functionally connected with the superior parietal cortex, paracentral lobule, and motor cortex, suggesting a sensorimotor region; (ii) the central precuneus, functionally connected to the dorsolateral prefrontal, dorsomedial prefrontal, and multimodal lateral inferior parietal cortex, suggesting a cognitive/associative region; and (iii) the posterior precuneus, displaying functional connectivity with adjacent visual cortical regions. These functional connectivity patterns were differentiated from the more ventral networks associated with the posterior cingulate, which connected with limbic structures such as the medial temporal cortex, dorsal and ventromedial prefrontal regions, posterior lateral inferior parietal regions, and the lateral temporal cortex. Our findings are consistent with predictions from anatomical tracer studies in the monkey, and provide support that resting-state functional connectivity (RSFC) may in part reflect underlying anatomy. These subdivisions within the precuneus suggest that neuroimaging studies will benefit from treating this region as anatomically (and thus functionally) heterogeneous. Furthermore, the consistency between functional connectivity networks in monkeys and humans provides support for RSFC as a viable tool for addressing cross-species comparisons of functional neuroanatomy.

Intrinsic fluctuations within cortical systems account for intertrial variability in human behavior.

The resting brain is not silent, but exhibits organized fluctuations in neuronal activity even in the absence of tasks or stimuli. This intrinsic brain activity persists during task performance and contributes to variability in evoked brain responses. What is unknown is if this intrinsic activity also contributes to variability in behavior. In the current fMRI study, we identify a relationship between human brain activity in the left somatomotor cortex and spontaneous trial-to-trial variability in button press force. We then demonstrate that 74% of this brain-behavior relationship is attributable to ongoing fluctuations in intrinsic activity similar to those observed during resting fixation. In addition to establishing a functional and behavioral significance of intrinsic brain activity, these results lend new insight into the origins of variability in human behavior.

Breakdown of functional connectivity in frontoparietal networks underlies behavioral deficits in spatial neglect.

Spatial neglect is a syndrome following stroke manifesting attentional deficits in perceiving and responding to stimuli in the contralesional field. We examined brain network integrity in patients with neglect by measuring coherent fluctuations of fMRI signals (functional connectivity). Connectivity in two largely separate attention networks located in dorsal and ventral frontoparietal areas was assessed at both acute and chronic stages of recovery. Connectivity in the ventral network, part of which directly lesioned, was diffusely disrupted and showed no recovery. In the structurally intact dorsal network, interhemispheric connectivity in posterior parietal cortex was acutely disrupted but fully recovered. This acute disruption, and disrupted connectivity in specific pathways in the ventral network, strongly correlated with impaired attentional processing across subjects. Lastly, disconnection of the white matter tracts connecting frontal and parietal cortices was associated with more severe neglect and more disrupted functional connectivity. These findings support a network view in understanding neglect.

Disruption of large-scale brain systems in advanced aging.

Cognitive decline is commonly observed in advanced aging even in the absence of disease. Here we explore the possibility that normal aging is accompanied by disruptive alterations in the coordination of large-scale brain systems that support high-level cognition. In 93 adults aged 18 to 93, we demonstrate that aging is characterized by marked reductions in normally present functional correlations within two higher-order brain systems. Anterior to posterior components within the default network were most severely disrupted with age. Furthermore, correlation reductions were severe in older adults free from Alzheimer's disease (AD) pathology as determined by amyloid imaging, suggesting that functional disruptions were not the result of AD. Instead, reduced correlations were associated with disruptions in white matter integrity and poor cognitive performance across a range of domains. These results suggest that cognitive decline in normal aging arises from functional disruption in the coordination of large-scale brain systems that support cognition.

Plasmid DNA fermentation strain and process-specific effects on vector yield, quality, and transgene expression.

Industrial plasmid DNA manufacturing processes are needed to meet the quality, economy, and scale requirements projected for future commercial products. We report development of a modified plasmid fermentation copy number induction profile that increases gene vaccination/therapy vector yields up to 2,600 mg/L. We determined that, in contrast to recombinant protein production, secretion of the metabolic byproduct acetate into the media had only a minor negative effect on plasmid replication. We also investigated the impact of differences in epigenetic dcm methylase-directed cytosine methylation on plasmid production, transgene expression, and immunogenicity. While Escherichia coli plasmid production yield and quality are unaffected, dcm- versions of CMV and CMV-HTLV-I R promoter plasmids had increased transgene expression in human cells. Surprisingly, despite improved expression, dcm- plasmid is less immunogenic. Our results demonstrate that it is critical to lock the plasmid methylation pattern (i.e., production strain) early in product development and that dcm- strains may be superior for gene therapy applications wherein reduced immunogenicity is desirable and for in vitro transient transfection applications such as AAV production where improved expression is beneficial.

A Predictive Model for Severe COVID-19 in the Medicare Population: A Tool for Prioritizing Primary and Booster COVID-19 Vaccination.

Recommendations for prioritizing COVID-19 vaccination have focused on the elderly at higher risk for severe disease. Existing models for identifying higher-risk individuals lack the needed integration of socio-demographic and clinical risk factors. Using multivariate logistic regression and random forest modeling, we developed a predictive model of severe COVID-19 using clinical data from Medicare claims for 16 million Medicare beneficiaries and socio-economic data from the CDC Social Vulnerability Index. Predicted individual probabilities of COVID-19 hospitalization were then calculated for population risk stratification and vaccine prioritization and mapping. The leading COVID-19 hospitalization risk factors were non-white ethnicity, end-stage renal disease, advanced age, prior hospitalization, leukemia, morbid obesity, chronic kidney disease, lung cancer, chronic liver disease, pulmonary fibrosis or pulmonary hypertension, and chemotherapy. However, previously reported risk factors such as chronic obstructive pulmonary disease and diabetes conferred modest hospitalization risk. Among all social vulnerability factors, residence in a low-income zip code was the only risk factor independently predicting hospitalization. This multifactor risk model and its population risk dashboard can be used to optimize COVID-19 vaccine allocation in the higher-risk Medicare population.

Using Deep Learning to Identify High-Risk Patients with Heart Failure with Reduced Ejection Fraction.

Background: Deep Learning (DL) has not been well-established as a method to identify high-risk patients among patients with heart failure (HF). Objectives: This study aimed to use DL models to predict hospitalizations, worsening HF events, and 30-day and 90-day readmissions in patients with heart failure with reduced ejection fraction (HFrEF). Methods: We analyzed the data of adult HFrEF patients from the IBM® MarketScan® Commercial and Medicare Supplement databases between January 1, 2015 and December 31, 2017. A sequential model architecture based on bi-directional long short-term memory (Bi-LSTM) layers was utilized. For DL models to predict HF hospitalizations and worsening HF events, we utilized two study designs: with and without a buffer window. For comparison, we also tested multiple traditional machine learning models including logistic regression, random forest, and eXtreme Gradient Boosting (XGBoost). Model performance was assessed by area under the curve (AUC) values, precision, and recall on an independent testing dataset. Results: A total of 47 498 HFrEF patients were included; 9427 with at least one HF hospitalization. The best AUCs of DL models without a buffer window in predicting HF hospitalizations and worsening HF events in the total patient cohort were 0.977 and 0.972; with a 7-day buffer window the best AUCs were 0.573 and 0.608, respectively. The best AUCs in predicting 30- and 90-day readmissions in all adult patients were 0.597 and 0.614, respectively. An AUC of 0.861 was attained for prediction of 90-day readmission in patients aged 18-64. For all outcomes assessed, the DL approach outperformed traditional machine learning models. Discussion: The DL approach can automate feature engineering during the model learning, which can increase the clinical applicability and lead to comparable or better model performance. However, the lack of granular clinical data, and sample size and imbalance issues may have limited the model's performance. Conclusions: A DL approach using Bi-LSTM was shown to be a feasible and useful tool to predict HF-related outcomes. This study can help inform the future development and deployment of predictive tools to identify high-risk HFrEF patients and ultimately facilitate targeted interventions in clinical practice.

Functional connectivity of the macaque posterior parahippocampal cortex.

Neuroimaging experiments in humans suggest that regions in parietal cortex and along the posterior midline are functionally connected to the medial temporal lobe and are active during memory retrieval. It is unknown whether macaques have a similar network. We examined functional connectivity in isoflurane-anesthetized macaques to identify a network associated with posterior parahippocampal cortex (PPHC). Functional connectivity was observed between the PPHC and retrosplenial, posterior cingulate, superior temporal gyrus, and inferior parietal cortex. PPHC correlations were distinct from regions in parietal and temporal cortex activated by an oculomotor task. Comparison of macaque and human PPHC correlations revealed similarities that suggest the temporal-parietal region identified in the macaque may share a common lineage with human Brodmann area 39, a region thought to be involved in recollection. These results suggest that macaques and humans may have homologous PPHC-parietal pathways. By specifying the location of the putative macaque homologue in parietal cortex, we provide a target for future physiological exploration of this area's role in mnemonic or alternative processes.

Critical design criteria for minimal antibiotic-free plasmid vectors necessary to combine robust RNA Pol II and Pol III-mediated eukaryotic expression with high bacterial production yields.

BACKGROUND: For safety considerations, regulatory agencies recommend the elimination of antibiotic resistance markers and non-essential sequences from plasmid DNA-based gene medicines. In the present study, we analyzed antibiotic-free (AF) vector design criteria impacting upon bacterial production and mammalian transgene expression. METHODS: Both CMV-HTLV-I R RNA Pol II promoter (protein transgene) and murine U6 RNA Pol III promoter (RNA transgene) vector designs were studied. Plasmid production yield was assessed through inducible fed-batch fermentation. RNA Pol II-directed enhanced green fluorescent protein and RNA Pol III-directed RNA expression were quantified by fluorometry and quantitative real-time polymerase chain reaction, respectively, after transfection of human HEK293 cells. RESULTS: Sucrose-selectable minimalized protein and therapeutic RNA expression vector designs that combined an RNA-based AF selection with highly productive fermentation manufacturing (>1000 mg/l plasmid DNA) and high-level in vivo expression of encoded products were identified. The AF selectable marker was also successfully applied to convert existing kanamycin-resistant DNA vaccine plasmids gWIZ and pVAX1 into AF vectors, demonstrating a general utility for retrofitting existing vectors. A minimum vector size for high yield plasmid fermentation was identified. A strategy for stable fermentation of plasmid dimers with improved vector potency and fermentation yields up to 1740 mg/l was developed. CONCLUSIONS: We report the development of potent high yield AF gene medicine expression vectors for protein or RNA (e.g. short hairpin RNA or microRNA) products. These AF expression vectors were optimized to exceed a newly-identified size threshold for high copy plasmid replication and direct higher transgene expression levels than alternative vectors.

Distinct brain networks for adaptive and stable task control in humans.

Control regions in the brain are thought to provide signals that configure the brain's moment-to-moment information processing. Previously, we identified regions that carried signals related to task-control initiation, maintenance, and adjustment. Here we characterize the interactions of these regions by applying graph theory to resting state functional connectivity MRI data. In contrast to previous, more unitary models of control, this approach suggests the presence of two distinct task-control networks. A frontoparietal network included the dorsolateral prefrontal cortex and intraparietal sulcus. This network emphasized start-cue and error-related activity and may initiate and adapt control on a trial-by-trial basis. The second network included dorsal anterior cingulate/medial superior frontal cortex, anterior insula/frontal operculum, and anterior prefrontal cortex. Among other signals, these regions showed activity sustained across the entire task epoch, suggesting that this network may control goal-directed behavior through the stable maintenance of task sets. These two independent networks appear to operate on different time scales and affect downstream processing via dissociable mechanisms.

Plasmid DNA production combining antibiotic-free selection, inducible high yield fermentation, and novel autolytic purification.

DNA vaccines and gene medicines, derived from bacterial plasmids, are emerging as an important new class of pharmaceuticals. However, the challenges of performing cell lysis processes for plasmid DNA purification at an industrial scale are well known. To address downstream purification challenges, we have developed autolytic Escherichia coli host strains that express endolysin (phage lambdaR) in the cytoplasm. Expression of the endolysin is induced during fermentation by a heat inducible promoter. The endolysin remains in the cytoplasm, where it is separated from its peptidoglycan substrate in the cell wall; hence the cells remain alive and intact and can be harvested by the usual methods. The plasmid DNA is then recovered by autolytic extraction under slightly acidic, low salt buffer conditions and treatment with a low concentration of non-ionic detergent. Under these conditions the E. coli genomic DNA remains associated with the insoluble cell debris and is removed by a solid-liquid separation. Here, we report fermentation, lysis methods, and plasmid purification using autolytic hosts.

Moving GLM ballistocardiogram artifact reduction for EEG acquired simultaneously with fMRI.

OBJECTIVE: Simultaneous acquisition of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) enables studies of brain activity at both high temporal and high spatial resolution. However, EEG acquired in a magnetic field is contaminated by ballistocardiogram (BKG) artifact. The most commonly used method of BKG artifact reduction, averaged artifact subtraction (AAS), was not designed to account for overlapping BKG waveforms generated by adjacent beats. We describe a new method based on a moving general linear model (mGLM) that accounts for overlapping BKG waveforms. METHODS: Simultaneous EEG-fMRI at 3 Tesla was performed in nine normal human subjects (8-11 runs/subject, 5.52 min/run). Gradient switching artifact was effectively reduced using commercially supplied procedures. Cardiac beats were detected using a novel correlation detector algorithm applied to the EKG trace. BKG artifact was reduced using both mGLM and AAS. RESULTS: mGLM recovered BKG waveforms outlasting the median inter-beat interval. mGLM more effectively than AAS removed variance in the EEG attributable to BKG artifact. CONCLUSIONS: mGLM offers advantages over AAS especially in the presence of variable heart rate. SIGNIFICANCE: The BKG artifact reduction procedure described herein improves the technique of simultaneous EEG-fMRI. Potential applications include basic investigations of the relationship between scalp potentials and functional imaging signals as well as clinical localization of epileptic foci.

Seeing faces is necessary for face-domain formation.

Here we report that monkeys raised without exposure to faces did not develop face domains, but did develop domains for other categories and did show normal retinotopic organization, indicating that early face deprivation leads to a highly selective cortical processing deficit. Therefore, experience must be necessary for the formation (or maintenance) of face domains. Gaze tracking revealed that control monkeys looked preferentially at faces, even at ages prior to the emergence of face domains, but face-deprived monkeys did not, indicating that face looking is not innate. A retinotopic organization is present throughout the visual system at birth, so selective early viewing behavior could bias category-specific visual responses toward particular retinotopic representations, thereby leading to domain formation in stereotyped locations in inferotemporal cortex, without requiring category-specific templates or biases. Thus, we propose that environmental importance influences viewing behavior, viewing behavior drives neuronal activity, and neuronal activity sculpts domain formation.

Development of the macaque face-patch system.

Face recognition is highly proficient in humans and other social primates; it emerges in infancy, but the development of the neural mechanisms supporting this behaviour is largely unknown. We use blood-volume functional MRI to monitor longitudinally the responsiveness to faces, scrambled faces, and objects in macaque inferotemporal cortex (IT) from 1 month to 2 years of age. During this time selective responsiveness to monkey faces emerges. Some functional organization is present at 1 month; face-selective patches emerge over the first year of development, and are remarkably stable once they emerge. Face selectivity is refined by a decreasing responsiveness to non-face stimuli.

Novel domain formation reveals proto-architecture in inferotemporal cortex.

Primate inferotemporal cortex is subdivided into domains for biologically important categories, such as faces, bodies and scenes, as well as domains for culturally entrained categories, such as text or buildings. These domains are in stereotyped locations in most humans and monkeys. To ask what determines the locations of such domains, we intensively trained seven juvenile monkeys to recognize three distinct sets of shapes. After training, the monkeys developed regions that were selectively responsive to each trained set. The location of each specialization was similar across monkeys, despite differences in training order. This indicates that the location of training effects does not depend on function or expertise, but rather on some kind of proto-organization. We explore the possibility that this proto-organization is retinotopic or shape-based.

Modulation of the brain's functional network architecture in the transition from wake to sleep.

The transition from quiet wakeful rest to sleep represents a period over which attention to the external environment fades. Neuroimaging methodologies have provided much information on the shift in neural activity patterns in sleep, but the dynamic restructuring of human brain networks in the transitional period from wake to sleep remains poorly understood. Analysis of electrophysiological measures and functional network connectivity of these early transitional states shows subtle shifts in network architecture that are consistent with reduced external attentiveness and increased internal and self-referential processing. Further, descent to sleep is accompanied by the loss of connectivity in anterior and posterior portions of the default-mode network and more locally organized global network architecture. These data clarify the complex and dynamic nature of the transitional period between wake and sleep and suggest the need for more studies investigating the dynamics of these processes.

Learning and memory: while you rest, your brain keeps working.

A recent study shows that brain activity recorded while the human subject is at 'rest' is significantly affected by a prior learning episode. These results suggest that understanding resting brain activity may be critical to understanding how humans learn from experience.