Working with Institutional Records: An Overview of a Project at the Mpls Institute of Arts

Before implementing wide-scale technology to organize institutional records, you must first have a strategy for the identification and arrangement of these intellectual assets. Establishing an archives/records management program is a preliminary cornerstone to future initiatives that focus on digital technologies. Hear from the Library & Archives staff at the Minneapolis Institute of Arts about their work on an NHPRC grant project to gain intellectual control over their institution’s documentary holdings

Novel Eurasian Highly Pathogenic Avian Influenza A H5 Viruses in Wild Birds, Washington, USA, 2014

The novel Eurasian lineage clade 2.3.4.4 highly pathogenic avian influenza (HPAI) A(H5N8) virus (http://www.who.int/influenza/gisrs_laboratory/h5_nomenclature_clade2344/en/) spread rapidly and globally during 2014, substantially affecting poultry populations. The first outbreaks were reported during January 2014 in chickens and domestic ducks in South Korea and subsequently in China and Japan (1–4), reaching Germany, the Netherlands, and the United Kingdom by November 2014 and Italy in early December 2014 (5). Also in November 2014, a novel HPAI H5N2 virus was reported in outbreaks on chicken and turkey farms in Fraser Valley, British Columbia, Canada (5). This H5N2 influenza virus is a reassortant that contains the Eurasian clade 2.3.4.4 H5 plus 4 other Eurasian genes (polymerase acidic protein subunit, matrix protein, polymerase basic protein subunit [PB] 2, nonstructural protein) and 3 North American wild bird lineage genes (neuraminidase [NA], nucleoprotein, PB1) (5). Taiwan has recently reported novel reassortants of the H5 clade 2.3.4.4 with other Eurasian viruses (H5N2, H5N3)

Association of physical function with predialysis blood pressure in patients on hemodialysis

BACKGROUND: New information from various clinical settings suggests that tight blood pressure control may not reduce mortality and may be associated with more side effects. METHODS: We performed cross-sectional multivariable ordered logistic regression to examine the association between predialysis blood pressure and the short physical performance battery (SPPB) in a cohort of 749 prevalent hemodialysis patients in the San Francisco and Atlanta areas recruited from July 2009 to August 2011 to study the relationship between systolic blood pressure and objective measures of physical function. Mean blood pressure for three hemodialysis sessions was analyzed in the following categories: <110 mmHg, 110-129 mmHg (reference), 130-159 mmHg, and ≥160 mmHg. SPPB includes three components: timed repeated chair stands, timed 15-ft walk, and balance tests. SPPB was categorized into ordinal groups (≤6, 7-9, 10-12) based on prior literature. RESULTS: Patients with blood pressure 130-159 mmHg had lower odds (OR 0.57, 95% CI 0.35-0.93) of scoring in a lower SPPB category than those whose blood pressure was between 110 and 129 mmHg, while those with blood pressure ≥160 mmHg had 0.56 times odds (95% CI 0.33-0.94) of scoring in a lower category when compared with blood pressure 110-129 mmHg. When individual components were examined, blood pressure was significantly associated with chair stand (130-159 mmHg: OR 0.59, 95% CI 0.38-0.92) and gait speed (≥160 mmHg: OR 0.59, 95% CI 0.35-0.98). Blood pressure ≥160 mmHg was not associated with substantially higher SPPB score compared with 130-159 mmHg. CONCLUSIONS: Patients with systolic blood pressure at or above 130 mmHg had better physical performance than patients with lower blood pressure in the normotensive range. The risk-benefit tradeoff of aggressive blood pressure control, particularly in low-functioning patients, should be reexamined

TEF, Vol. 4 No. 1

This is the fourth issue of the annually published literary magazine TEF.https://scholarworks.sfasu.edu/tef/1003/thumbnail.jp

A Search for Technosignatures Around 11,680 Stars with the Green Bank Telescope at 1.15-1.73 GHz

We conducted a search for narrowband radio signals over four observing sessions in 2020-2023 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. We pointed the telescope in the directions of 62 TESS Objects of Interest, capturing radio emissions from a total of ~11,680 stars and planetary systems in the ~9 arcminute beam of the telescope. All detections were either automatically rejected or visually inspected and confirmed to be of anthropogenic nature. In this work, we also quantified the end-to-end efficiency of radio SETI pipelines with a signal injection and recovery analysis. The UCLA SETI pipeline recovers 94.0% of the injected signals over the usable frequency range of the receiver and 98.7% of the injections when regions of dense RFI are excluded. In another pipeline that uses incoherent sums of 51 consecutive spectra, the recovery rate is ~15 times smaller at ~6%. The pipeline efficiency affects calculations of transmitter prevalence and SETI search volume. Accordingly, we developed an improved Drake Figure of Merit and a formalism to place upper limits on transmitter prevalence that take the pipeline efficiency and transmitter duty cycle into account. Based on our observations, we can state at the 95% confidence level that fewer than 6.6% of stars within 100 pc host a transmitter that is detectable in our search (EIRP > 1e13 W). For stars within 20,000 ly, the fraction of stars with detectable transmitters (EIRP > 5e16 W) is at most 3e-4. Finally, we showed that the UCLA SETI pipeline natively detects the signals detected with AI techniques by Ma et al. (2023).Comment: 22 pages, 9 figures, submitted to AJ, revise

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. Practitioner Points: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.</p

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. Practitioner Points: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.</p

GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors

Objective: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and crossvalidated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS metaanalysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. Methods: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. Results: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values &lt;5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. Conclusions: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.</p

Fulminant corticobasal degeneration: a distinct variant with predominant neuronal tau aggregates.

Corticobasal degeneration typically progresses gradually over 5-7 years from onset till death. Fulminant corticobasal degeneration cases with a rapidly progressive course were rarely reported (RP-CBD). This study aimed to investigate their neuropathological characteristics. Of the 124 autopsy-confirmed corticobasal degeneration cases collected from 14 centres, we identified 6 RP-CBD cases (4.8%) who died of advanced disease within 3 years of onset. These RP-CBD cases had different clinical phenotypes including rapid global cognitive decline (N = 2), corticobasal syndrome (N = 2) and Richardson's syndrome (N = 2). We also studied four corticobasal degeneration cases with an average disease duration of 3 years or less, who died of another unrelated illness (Intermediate-CBD). Finally, we selected 12 age-matched corticobasal degeneration cases out of a cohort of 110, who had a typical gradually progressive course and reached advanced clinical stage (End-stage-CBD). Quantitative analysis showed high overall tau burden (p = 0.2) and severe nigral cell loss (p = 0.47) in both the RP-CBD and End-stage-CBD groups consistent with advanced pathological changes, while the Intermediate-CBD group (mean disease duration = 3 years) had milder changes than End-stage-CBD (p < 0.05). These findings indicated that RP-CBD cases had already developed advanced pathological changes as those observed in End-stage-CBD cases (mean disease duration = 6.7 years), but within a significantly shorter duration (2.5 years; p < 0.001). Subgroup analysis was performed to investigate the cellular patterns of tau aggregates in the anterior frontal cortex and caudate by comparing neuronal-to-astrocytic plaque ratios between six RP-CBD cases, four Intermediate-CBD and 12 age-matched End-stage-CBD. Neuronal-to-astrocytic plaque ratios of Intermediate-CBD and End-stage-CBD, but not RP-CBD, positively correlated with disease duration in both the anterior frontal cortex and caudate (p = 0.02). In contrast to the predominance of astrocytic plaques we previously reported in preclinical asymptomatic corticobasal degeneration cases, neuronal tau aggregates predominated in RP-CBD exceeding those in Intermediate-CBD (anterior frontal cortex: p < 0.001, caudate: p = 0.001) and End-stage-CBD (anterior frontal cortex: p = 0.03, caudate: p = 0.01) as demonstrated by its higher neuronal-to-astrocytic plaque ratios in both anterior frontal cortex and caudate. We did not identify any difference in age at onset, any pathogenic tau mutation or concomitant pathologies that could have contributed to the rapid progression of these RP-CBD cases. Mild TDP-43 pathology was observed in three RP-CBD cases. All RP-CBD cases were men. The MAPT H2 haplotype, known to be protective, was identified in one RP-CBD case (17%) and 8 of the matched End-stage-CBD cases (67%). We conclude that RP-CBD is a distinct aggressive variant of corticobasal degeneration with characteristic neuropathological substrates resulting in a fulminant disease process as evident both clinically and pathologically. Biological factors such as genetic modifiers likely play a pivotal role in the RP-CBD variant and should be the subject of future research