Evolutionary prediction is of deep practical and philosophical importance. Here we show, using a simple computational protein model, that protein evolution remains unpredictable, even if one knows the effects of all mutations in an ancestral protein background. We performed a virtual deep mutational scan-revealing the individual and pairwise epistatic effects of every mutation to our model protein-and then used this information to predict evolutionary trajectories. Our predictions were poor. This is a consequence of statistical thermodynamics. Proteins exist as ensembles of similar conformations. The effect of a mutation depends on the relative probabilities of conformations in the ensemble, which in turn, depend on the exact amino acid sequence of the protein. Accumulating substitutions alter the relative probabilities of conformations, thereby changing the effects of future mutations. This manifests itself as subtle but pervasive high-order epistasis. Uncertainty in the effect of each mutation accumulates and undermines prediction. Because conformational ensembles are an inevitable feature of proteins, this is likely universal.
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http://dx.doi.org/10.1073/pnas.1711927114 | DOI Listing |
Cancer Causes Control
January 2025
Surveillance and Health Equity Science, American Cancer Society, Kennesaw, GA, USA.
Purpose: Oncological treatments, such as radiotherapy, which requires consistent electricity, the presence of specialized clinical teams, and daily patient access to treatment facilities, are frequently disrupted by extreme weather events, posing several health hazards to patients. This study explores the association between declared wildfire disasters during radiotherapy and overall survival among patients with non-small cell lung cancer (NSCLC).
Methods: The study population consisted of 202,935 adults with inoperable Stage III NSCLC, who initiated radiotherapy from 2004 through 2019.
Eur Respir Rev
January 2025
Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.
Introduction: Numerous studies have characterised trajectories of asthma and allergy in children using machine learning, but with different techniques and mixed findings. The present work aimed to summarise the evidence and critically appraise the methodology.
Methods: 10 databases were searched.
Diabetes Metab Syndr
January 2025
Endocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Objective: To explore the effects of lifestyle interventions on the prevention of type 2 diabetes (T2D) and reversion to normoglycemia by prediabetes phenotype.
Methods: We searched MEDLINE, Embase, and the Cochrane Library for randomized controlled trials (RCTs) that evaluated the effects of lifestyle interventions in adults with prediabetes for a minimum duration of one year. Two reviewers independently screened articles, extracted data, and performed quality assessment.
Clin Orthop Relat Res
January 2025
Department of Orthopaedic Surgery, Mayo Clinic, Jacksonville, FL, USA.
Background: A variety of clinically important benchmarks of success (CIBS) have been defined for total shoulder arthroplasty (TSA) to quantify success. However, it is unclear how the preoperative status of the patient influences their likelihood of achieving each CIBS.
Questions/purposes: (1) What proportion of patients achieve commonly used CIBS after TSA? (2) Is there a relationship between a patients' preoperative function and their probability of achieving different CIBS? (3) Does there exist preoperative ranges for each outcome measure that are associated with greater achievement of CIBS?
Methods: We retrospectively queried a multicenter shoulder arthroplasty database for primary anatomic TSA (aTSA) and reverse TSA (rTSA).
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