Science at risk? Considering the importance of academic freedom for STEM research production across 17 OECD countries.

Since 2011, a declining trend in academic freedom globally has paralleled a rising tide of neo-nationalism. We use fixed effects models to examine data from the Varieties of Democracy (V-DEM) academic freedom index and bibliometric data for 17 OECD countries across nearly three decades (1981-2007) that precede the recent decline in academic freedom. We find substantial, statistically significant, positive relationships between cross-nationally comparable and longitudinal measures of academic freedom and volume of STEM publications. Additionally, academic freedom positively influenced the quality of STEM publications as measured by journal rankings. Our findings were relatively consistent across various measures of academic freedom and model specifications. We discuss implications for safeguarding academic freedom, applying neo-institutional theory, and identifying directions for future research.

Evaluating statistical significance in a meta-analysis by using numerical integration.

Meta-analysis is a method for enhancing statistical power through the integration of information from multiple studies. Various methods for integrating p-values (i.e., statistical significance), including Fisher's method under an independence assumption, the permutation method, and the decorrelation method, have been broadly used in bioinformatics and computational biotechnology studies. However, these methods have limitations related to statistical assumption, computing efficiency, and accuracy of statistical significance estimation. In this study, we proposed a numerical integration method and examined its theoretical properties. Simulation studies were conducted to evaluate its Type I error, statistical power, computational efficiency, and estimation accuracy, and the results were compared with those of other methods. The results demonstrate that our proposed method performs well in terms of Type I error, statistical power, computing efficiency (regardless of sample size), and statistical significance estimation accuracy. P-value data from multiple large-scale genome-wide association studies (GWASs) and transcriptome-wise association studies (TWASs) were analyzed. The results demonstrate that our proposed method can be used to identify critical genomic regions associated with rheumatoid arthritis and asthma, increase statistical significance in individual GWASs and TWASs, and control for false-positives more effectively than can Fisher's method under an independence assumption. We created the software package Pbine, available at GitHub (https://github.com/Yinchun-Lin/Pbine).

Subtyping of major SARS-CoV-2 variants reveals different transmission dynamics based on 10 million genomes.

SARS-CoV-2 continues to evolve, causing waves of the pandemic. Up to May 2022, 10 million genome sequences have accumulated, which are classified into five major variants of concern. With the growing number of sequenced genomes, analysis of the big dataset has become increasingly challenging. Here we developed systematic approaches based on sets of correlated single nucleotide variations (SNVs) for comprehensive subtyping and pattern recognition of transmission dynamics. The approach outperformed single-SNV and spike-centric scans. Moreover, the derived subtypes elucidate the relationship of signature SNVs and transmission dynamics. We found that different subtypes of the same variant, including Delta and Omicron exhibited distinct temporal trajectories. For example, some Delta and Omicron subtypes did not spread rapidly, while others did. We identified sets of characteristic SNVs that appeared to enhance transmission or decrease efficacy of antibodies for some subtypes. We also identified a set of SNVs that appeared to suppress transmission or increase viral sensitivity to antibodies. For the Omicron variant, the dominant type in the world, we identified the subtypes with enhanced and suppressed transmission in an analysis of eight million genomes as of March 2022 and further confirmed the findings in a later analysis of ten million genomes as of May 2022. While the "enhancer" SNVs exhibited an enriched presence on the spike protein, the "suppressor" SNVs are mainly elsewhere. Disruption of the SNV correlation largely destroyed the enhancer-suppressor phenomena. These results suggest the importance of fine subtyping of variants, and point to potential complex interactions among SNVs.

Analysis of genomic distributions of SARS-CoV-2 reveals a dominant strain type with strong allelic associations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of COVID 19, continues to evolve since its first emergence in December 2019. Using the complete sequences of 1,932 SARS-CoV-2 genomes, various clustering analyses consistently identified six types of the strains. Independent of the dendrogram construction, 13 signature variations in the form of single nucleotide variations (SNVs) in protein coding regions and one SNV in the 5' untranslated region (UTR) were identified and provided a direct interpretation for the six types (types I to VI). The six types of the strains and their underlying signature SNVs were validated in two subsequent analyses of 6,228 and 38,248 SARS-CoV-2 genomes which became available later. To date, type VI, characterized by the four signature SNVs C241T (5'UTR), C3037T (nsp3 F924F), C14408T (nsp12 P4715L), and A23403G (Spike D614G), with strong allelic associations, has become the dominant type. Since C241T is in the 5' UTR with uncertain significance and the characteristics can be captured by the other three strongly associated SNVs, we focus on the other three. The increasing frequency of the type VI haplotype 3037T-14408T-23403G in the majority of the submitted samples in various countries suggests a possible fitness gain conferred by the type VI signature SNVs. The fact that strains missing one or two of these signature SNVs fail to persist implies possible interactions among these SNVs. Later SNVs such as G28881A, G28882A, and G28883C have emerged with strong allelic associations, forming new subtypes. This study suggests that SNVs may become an important consideration in SARS-CoV-2 classification and surveillance.

Prolonged treatment time deteriorates positioning accuracy for stereotactic radiosurgery.

INTRODUCTION: The accuracy of radiation delivery is increasingly important as radiotherapy technology continues to develop. The goal of this study was to evaluate intrafractional motion during intracranial radiosurgery and the relationship between motion change and treatment time. METHODS AND MATERIALS: A total of 50 treatment records with 5988 images, all acquired during treatments with the CyberKnife Radiosurgery System, were retrospectively analyzed in this study. We measured translation and rotation motion including superior-inferior (SI), right-left (RL), anterior-posterior (AP), roll, tilt and yaw. All of the data was obtained during the first 45 minutes of treatment. The records were divided into 3 groups based on 15-min time intervals following the beginning of treatment: group A (0-15 min), group B (16-30 min) and group C (31-45 min). The mean deviations, systematic errors, random errors and margin for planning target volume (PTV) were calculated for each group. RESULTS: The mean deviations were less than 0.1 mm in all three translation directions in the first 15 minutes. Greater motion occurred with longer treatment times, especially in the SI direction. For the 3D vector, a time-dependent change was observed, from 0.34 mm to 0.77 mm (p=0.01). There was no significant correlation between the treatment time and deviations in the AP, LR and rotation axes. Longer treatment times were associated with increases in systematic error, but not in random error. The estimated PTV margin for groups A, B and C were 0.86 / 1.14 / 1.31 mm, 0.75 / 1.12 / 1.20 mm, and 0.43 / 0.54 / 0.81 mm in the SI, RL, and AP directions, respectively. CONCLUSIONS: During intracranial radiosurgery, a consistent increase in the positioning deviation over time was observed, especially in the SI direction. If treatment time is greater than 15 minutes, we recommend increasing the PTV margins to ensure treatment precision.

A proteome reference map of Trichomonas vaginalis.

Trichomoniasis caused by Trichomonas vaginalis is the most common sexual transmitted infection in the world. The 170-MB genome of this protozoan contains 60,000 genes, the largest number of genes ever identified in protozoan. High-throughput expression sequenced tag analysis showed that at least 4,000 genes were expressed in the trophozoite stage. In the present study, we use two-dimensional electrophoresis combined with matrix-assisted laser desorption ionization time-of-flight mass spectrometry analysis to profile, identify, and characterize proteins expressed in the trophozoite stage of T. vaginalis. A total of 247 spots representing 164 different proteins were identified. The identified proteins with known sequence or motif/domain homologies were further classified into groups according to their biological functions. Among them, proteins related to carbohydrate metabolism represented the most abundant category in the T. vaginalis proteome. This study presented the most extensive proteomic analysis of T. vaginalis to date and provided a reference proteome database for future comparative proteomic studies.

TFIIH XPB mutants suggest a unified bacterial-like mechanism for promoter opening but not escape.

DNA helicases open the duplex during DNA replication, repair and transcription. However, RNA polymerase II is the only member of its family with this requirement; RNA polymerases I and III and bacterial RNA polymerases open DNA without a helicase. In this report, characterization of XPB mutants indicates that its helicase activity is not used for RNA polymerase II promoter opening, which is instead driven by its ATPase activity. The mutants have parallels in sigma(54) bacterial transcription and this suggests a similar mode of opening DNA for both RNA polymerases, involving ATP-dependent enzyme conformational changes. Promoter escape is defective in these XPB mutants, suggesting that the XPB helicase acts as an ATP-driven motor to reorganize the tightly wrapped multiprotein eukaryotic preinitiation complex during the remodeling that precedes elongation and the coupling to RNA processing events.