Widespread distribution of bacteria containing PETases with a functional motif across global oceans.

Accumulating evidence indicates that microorganisms respond to the ubiquitous plastic pollution by evolving plastic-degrading enzymes. However, the functional diversity of these enzymes and their distribution across the ocean, including the deep sea, remain poorly understood. By integrating bioinformatics and artificial intelligence-based structure prediction, we developed a structure- and function-informed algorithm to computationally distinguish functional polyethylene terephthalate-degrading enzymes (PETases) from variants lacking PETase activity (pseudo-PETase), either due to alternative substrate specificity or pseudogene origin.

Genomic insights into novel extremotolerant bacteria isolated from the NASA Phoenix mission spacecraft assembly cleanrooms.

Background: Human-designed oligotrophic environments, such as cleanrooms, harbor unique microbial communities shaped by selective pressures like temperature, humidity, nutrient availability, cleaning reagents, and radiation. Maintaining the biological cleanliness of NASA's mission-associated cleanrooms, where spacecraft are assembled and tested, is critical for planetary protection. Even with stringent controls such as regulated airflow, temperature management, and rigorous cleaning, resilient microorganisms can persist in these environments, posing potential risks for space missions.

Rapid evolution of SARS-CoV-2 challenges human defenses.

The race between pathogens and their hosts is a major evolutionary driver, where both reshuffle their genomes to overcome and reorganize the defenses for infection, respectively. Evolutionary theory helps formulate predictions on the future evolutionary dynamics of SARS-CoV-2, which can be monitored through unprecedented real-time tracking of SARS-CoV-2 population genomics at the global scale. Here we quantify the accelerating evolution of SARS-CoV-2 by tracking the SARS-CoV-2 mutation globally, with a focus on the Receptor Binding Domain (RBD) of the spike protein determining infection success.

Detection of SARS-CoV-2 variants requires urgent global coordination.

Objectives: To assess the efforts deployed by different nations and territories in sequencing SARS-CoV-2 isolates, thus enabling detection of variants, known and novel, of concern.

Methods: The sources of over one million full genome sequences of SARS-CoV-2 virus available in the COVID-19 virus Mutation Tracker (CovMT) were analyzed to determine the number of variants in the RBD region of the genome determining infectivity detected in the various nations and territories.

Results: The number of detected variants increased as the square root of sequencing effort by nations.

No Evidence for Temperature-Dependence of the COVID-19 Epidemic.

The pandemic of the COVID-19 extended from China across the north-temperate zone, and more recently to the tropics and southern hemisphere. The hypothesis that COVID-19 spread is temperature-dependent was tested based on data derived from nations across the world and provinces in China. No evidence of a pattern between spread rates and ambient temperature was found, suggesting that the SARS-CoV-2 is unlikely to behave as a seasonal respiratory virus.

Multiple stressor effects on coral reef ecosystems.

Global climate change has profound implications on species distributions and ecosystem functioning. In the coastal zone, ecological responses may be driven by various biogeochemical and physical environmental factors. Synergistic interactions can occur when the combined effects of stressors exceed their individual effects.

Marine heatwaves reveal coral reef zones susceptible to bleaching in the Red Sea.

As the Earth's temperature continues to rise, coral bleaching events become more frequent. Some of the most affected reef ecosystems are located in poorly monitored waters, and thus, the extent of the damage is unknown. We propose the use of marine heatwaves (MHWs) as a new approach for detecting coral reef zones susceptible to bleaching, using the Red Sea as a model system.

What Are the Odds? Modern Relevance and Bayes Factor Solutions for MacAlister's Problem From the 1881 .

In 1881, Donald MacAlister posed a problem in the that remains relevant today. The problem centers on the statistical evidence for the effectiveness of a treatment based on a comparison between two proportions. A brief historical sketch is followed by a discussion of two default Bayesian solutions, one based on a one-sided test between independent rates, and one on a one-sided test between dependent rates.

Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications.

Bayesian parameter estimation and Bayesian hypothesis testing present attractive alternatives to classical inference using confidence intervals and p values. In part I of this series we outline ten prominent advantages of the Bayesian approach. Many of these advantages translate to concrete opportunities for pragmatic researchers.

Bayesian inference for psychology. Part II: Example applications with JASP.

Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely.

Default "Gunel and Dickey" Bayes factors for contingency tables.

The analysis of R×C contingency tables usually features a test for independence between row and column counts. Throughout the social sciences, the adequacy of the independence hypothesis is generally evaluated by the outcome of a classical p-value null-hypothesis significance test. Unfortunately, however, the classical p-value comes with a number of well-documented drawbacks.

A unimodal species response model relating traits to environment with application to phytoplankton communities.

In this paper we attempt to explain observed niche differences among species (i.e. differences in their distribution along environmental gradients) by differences in trait values (e.

Generalized linear mixed models can detect unimodal species-environment relationships.

Niche theory predicts that species occurrence and abundance show non-linear, unimodal relationships with respect to environmental gradients. Unimodal models, such as the Gaussian (logistic) model, are however more difficult to fit to data than linear ones, particularly in a multi-species context in ordination, with trait modulated response and when species phylogeny and species traits must be taken into account. Adding squared terms to a linear model is a possibility but gives uninterpretable parameters.