Category: Nevin Manimala

Proc Natl Acad Sci U S A. 2024 Feb 27;121(9):e2313925121. doi: 10.1073/pnas.2313925121. Epub 2024 Feb 22.

ABSTRACT

We administer a Turing test to AI chatbots. We examine how chatbots behave in a suite of classic behavioral games that are designed to elicit characteristics such as trust, fairness, risk-aversion, cooperation, etc., as well as how they respond to a traditional Big-5 psychological survey that measures personality traits. ChatGPT-4 exhibits behavioral and personality traits that are statistically indistinguishable from a random human from tens of thousands of human subjects from more than 50 countries. Chatbots also modify their behavior based on previous experience and contexts “as if” they were learning from the interactions and change their behavior in response to different framings of the same strategic situation. Their behaviors are often distinct from average and modal human behaviors, in which case they tend to behave on the more altruistic and cooperative end of the distribution. We estimate that they act as if they are maximizing an average of their own and partner’s payoffs.

PMID:38386710 | DOI:10.1073/pnas.2313925121

Proc Natl Acad Sci U S A. 2024 Feb 27;121(9):e2313192121. doi: 10.1073/pnas.2313192121. Epub 2024 Feb 22.

ABSTRACT

Enzymes catalyze biochemical reactions through precise positioning of substrates, cofactors, and amino acids to modulate the transition-state free energy. However, the role of conformational dynamics remains poorly understood due to poor experimental access. This shortcoming is evident with Escherichia coli dihydrofolate reductase (DHFR), a model system for the role of protein dynamics in catalysis, for which it is unknown how the enzyme regulates the different active site environments required to facilitate proton and hydride transfer. Here, we describe ligand-, temperature-, and electric-field-based perturbations during X-ray diffraction experiments to map the conformational dynamics of the Michaelis complex of DHFR. We resolve coupled global and local motions and find that these motions are engaged by the protonated substrate to promote efficient catalysis. This result suggests a fundamental design principle for multistep enzymes in which pre-existing dynamics enable intermediates to drive rapid electrostatic reorganization to facilitate subsequent chemical steps.

PMID:38386706 | DOI:10.1073/pnas.2313192121

Cancer. 2024 Feb 22. doi: 10.1002/cncr.35264. Online ahead of print.

ABSTRACT

BACKGROUND: Survivors of rectal cancer experience persistent bowel dysfunction after treatments. Dietary interventions may be an effective approach for symptom management and posttreatment diet quality. SWOG S1820 was a pilot randomized trial of the Altering Intake, Managing Symptoms in Rectal Cancer (AIMS-RC) intervention for bowel dysfunction in survivors of rectal cancer.

METHODS: Ninety-three posttreatment survivors were randomized to the AIMS-RC group (N = 47) or the Healthy Living Education attention control group (N = 46) after informed consent and completion of a prerandomization run-in. Outcome measures were completed at baseline and at 18 and 26 weeks postrandomization. The primary end point was total bowel function score, and exploratory end points included low anterior resection syndrome (LARS) score, quality of life, dietary quality, motivation, self-efficacy, and positive/negative affect.

RESULTS: Most participants were White and college educated, with a mean age of 55.2 years and median time since surgery of 13.1 months. There were no statistically significant differences in total bowel function score by group, with the AIMS-RC group demonstrating statistically significant improvements in the exploratory end points of LARS (p = .01) and the frequency subscale of the bowel function index (p = .03). The AIMS-RC group reported significantly higher acceptability of the study.

CONCLUSIONS: SWOG S1820 did not provide evidence of benefit from the AIMS-RC intervention relative to the attention control. Select secondary end points did demonstrate improvements. The study was highly feasible and acceptable for participants in the National Cancer Institute Community Oncology Research Program. Findings provide strong support for further refinement and effectiveness testing of the AIMS-RC intervention.

PMID:38386696 | DOI:10.1002/cncr.35264

PLoS Comput Biol. 2024 Feb 22;20(2):e1011113. doi: 10.1371/journal.pcbi.1011113. Online ahead of print.

ABSTRACT

A variety of pulmonary insults can prompt the need for life-saving mechanical ventilation; however, misuse, prolonged use, or an excessive inflammatory response, can result in ventilator-induced lung injury. Past research has observed an increased instance of respiratory distress in older patients and differences in the inflammatory response. To address this, we performed high pressure ventilation on young (2-3 months) and old (20-25 months) mice for 2 hours and collected data for macrophage phenotypes and lung tissue integrity. Large differences in macrophage activation at baseline and airspace enlargement after ventilation were observed in the old mice. The experimental data was used to determine plausible trajectories for a mathematical model of the inflammatory response to lung injury which includes variables for the innate inflammatory cells and mediators, epithelial cells in varying states, and repair mediators. Classification methods were used to identify influential parameters separating the parameter sets associated with the young or old data and separating the response to ventilation, which was measured by changes in the epithelial state variables. Classification methods ranked parameters involved in repair and damage to the epithelial cells and those associated with classically activated macrophages to be influential. Sensitivity results were used to determine candidate in-silico interventions and these interventions were most impact for transients associated with the old data, specifically those with poorer lung health prior to ventilation. Model results identified dynamics involved in M1 macrophages as a focus for further research, potentially driving the age-dependent differences in all macrophage phenotypes. The model also supported the pro-inflammatory response as a potential indicator of age-dependent differences in response to ventilation. This mathematical model can serve as a baseline model for incorporating other pulmonary injuries.

PMID:38386693 | DOI:10.1371/journal.pcbi.1011113

PLoS Comput Biol. 2024 Feb 22;20(2):e1011878. doi: 10.1371/journal.pcbi.1011878. Online ahead of print.

ABSTRACT

Mutant selection windows (MSWs), the range of drug concentrations that select for drug-resistant mutants, have long been used as a model for predicting drug resistance and designing optimal dosing strategies in infectious disease. The canonical MSW model offers comparisons between two subtypes at a time: drug-sensitive and drug-resistant. In contrast, the fitness landscape model with N alleles, which maps genotype to fitness, allows comparisons between N genotypes simultaneously, but does not encode continuous drug response data. In clinical settings, there may be a wide range of drug concentrations selecting for a variety of genotypes in both cancer and infectious diseases. Therefore, there is a need for a more robust model of the pathogen response to therapy to predict resistance and design new therapeutic approaches. Fitness seascapes, which model genotype-by-environment interactions, permit multiple MSW comparisons simultaneously by encoding genotype-specific dose-response data. By comparing dose-response curves, one can visualize the range of drug concentrations where one genotype is selected over another. In this work, we show how N-allele fitness seascapes allow for N * 2N-1 unique MSW comparisons. In spatial drug diffusion models, we demonstrate how fitness seascapes reveal spatially heterogeneous MSWs, extending the MSW model to more fully reflect the selection of drug resistant genotypes. Furthermore, using synthetic data and empirical dose-response data in cancer, we find that the spatial structure of MSWs shapes the evolution of drug resistance in an agent-based model. By simulating a tumor treated with cyclic drug therapy, we find that mutant selection windows introduced by drug diffusion promote the proliferation of drug resistant cells. Our work highlights the importance and utility of considering dose-dependent fitness seascapes in evolutionary medicine.

PMID:38386690 | DOI:10.1371/journal.pcbi.1011878

PLoS Negl Trop Dis. 2024 Feb 22;18(2):e0011986. doi: 10.1371/journal.pntd.0011986. Online ahead of print.

ABSTRACT

BACKGROUND: Trachoma recrudescence after elimination as a public health problem has been reached is a concern for control programs globally. Programs typically conduct district-level trachoma surveillance surveys (TSS) ≥ 2 years after the elimination threshold is achieved to determine whether the prevalence of trachomatous inflammation-follicular (TF) among children ages 1 to 9 years remains <5%. Many TSS are resulting in a TF prevalence ≥5%. Once a district returns to TF ≥5%, a program typically restarts costly mass drug administration (MDA) campaigns and surveys at least twice, for impact and another TSS. In Amhara, Ethiopia, most TSS which result in a TF ≥5% have a prevalence close to 5%, making it difficult to determine whether the result is due to true recrudescence or to statistical variability. This study’s aim was to monitor recrudescence within Amhara by waiting to restart MDA within 2 districts with a TF prevalence ≥5% at TSS, Metema = 5.2% and Woreta Town = 5.1%. The districts were resurveyed 1 year later using traditional and alternative indicators, such as measures of infection and serology, a “wait and watch” approach.

METHODS/PRINCIPAL FINDINGS: These post-surveillance surveys, conducted in 2021, were multi-stage cluster surveys whereby certified graders assessed trachoma signs. Children ages 1 to 9 years provided a dried blood spot and children ages 1 to 5 years provided a conjunctival swab. TF prevalence in Metema and Woreta Town were 3.6% (95% Confidence Interval [CI]:1.4-6.4) and 2.5% (95% CI:0.8-4.5) respectively. Infection prevalence was 1.2% in Woreta Town and 0% in Metema. Seroconversion rates to Pgp3 in Metema and Woreta Town were 0.4 (95% CI:0.2-0.7) seroconversions per 100 child-years and 0.9 (95% CI:0.6-1.5) respectively.

CONCLUSIONS/SIGNIFICANCE: Both study districts had a TF prevalence <5% with low levels of Chlamydia trachomatis infection and transmission, and thus MDA interventions are no longer warranted. The wait and watch approach represents a surveillance strategy which could lead to fewer MDA campaigns and surveys and thus cost savings with reduced antibiotic usage.

PMID:38386689 | DOI:10.1371/journal.pntd.0011986

PLoS One. 2024 Feb 22;19(2):e0297874. doi: 10.1371/journal.pone.0297874. eCollection 2024.

ABSTRACT

Bayes factors for composite hypotheses have difficulty in encoding vague prior knowledge, as improper priors cannot be used and objective priors may be subjectively unreasonable. To address these issues I revisit the posterior Bayes factor, in which the posterior distribution from the data at hand is re-used in the Bayes factor for the same data. I argue that this is biased when calibrated against proper Bayes factors, but propose adjustments to allow interpretation on the same scale. In the important case of a regular normal model, the bias in log scale is half the number of parameters. The resulting empirical Bayes factor is closely related to the widely applicable information criterion. I develop test-based empirical Bayes factors for several standard tests and propose an extension to multiple testing closely related to the optimal discovery procedure. When only a P-value is available, an approximate empirical Bayes factor is 10p. I propose interpreting the strength of Bayes factors on a logarithmic scale with base 3.73, reflecting the sharpest distinction between weaker and stronger belief. This provides an objective framework for interpreting statistical evidence, and realises a Bayesian/frequentist compromise.

PMID:38386684 | DOI:10.1371/journal.pone.0297874

PLoS One. 2024 Feb 22;19(2):e0298810. doi: 10.1371/journal.pone.0298810. eCollection 2024.

ABSTRACT

INTRODUCTION: The novel coronavirus SARS-CoV-2 causes Coronavirus Disease 2019 (COVID-19). Vaccination has been identified as one of the most effective strategies for combating COVID-19. Positive perceptions and attitudes of HCPs towards the COVID-19 vaccination are essential to vaccine uptake and adherence. However, the perceptions and attitudes of HCPs towards the COVID-19 vaccination remain largely unexplored. We therefore assessed healthcare professionals’ perceptions, attitudes, and predictors of their attitudes towards COVID-19 vaccination in the Wa Municipality, Upper West Region of Ghana.

METHODS: In 2023, from January 16th to February 28th, we administered a multi-centre e-survey to a cross-section of 403 healthcare professionals in Wa Municipality of the Upper West Region, Ghana. We used STATA version 13 to analyze the data. Frequencies, percentages, and composite scores were used to assess perceptions and attitudes towards the COVID-19 vaccination. Hierarchical binary logistic regression modeling was then used to determine the predictors of attitudes towards the COVID-19 vaccination.

RESULTS: The healthcare professionals had positive perceptions [6.00; IQR = 4.00-7.00] and attitudes [5.00; IQR = 4.00-5.00] towards theCOVID-19 vaccination. Positive perception [aOR = 1.81; 95% CI = 1.14-2.87, p < 0.05], female sex [aOR = 0.58; 95% CI = 0.35-0.97, p < 0.05], marital status [aOR = 1.94; 95% CI = 1.20-3.12; p < 0.01], having a bachelor’s degree or higher [aOR = 2.03; 95% CI = 1.01-4.12; p < 0.05], and working in the Wa North sub-Municipal area [aOR = 0.22; 95% CI = 0.05-0.96; p < 0.05] were statistically significantly associated with attitudes towards COVID-19 vaccination.

CONCLUSION: The healthcare professionals’ perceptions and attitudes towards the COVID-19 vaccination were positive but suboptimal. We recommend regular education on COVID-19 vaccine benefits, safety, and efficacy. Enabling the work environment and addressing vaccine availability and accessibility for healthcare professionals should also be prioritized. These measures should particularly focus on female, single healthcare professionals who possess below a bachelor’s degree and are working in the Wa North sub-municipal area.

PMID:38386682 | DOI:10.1371/journal.pone.0298810

Stat Med. 2024 Mar 15;43(6):1170-1193. doi: 10.1002/sim.9999. Epub 2024 Jan 20.

ABSTRACT

This research introduces a multivariate τ $$ tau $$ -inflated beta regression ( τ $$ tau $$ -IBR) modeling approach for the analysis of censored recurrent event data that is particularly useful when there is a mixture of (a) individuals who are generally less susceptible to recurrent events and (b) heterogeneity in duration of event-free periods amongst those who experience events. The modeling approach is applied to a restructured version of the recurrent event data that consists of censored longitudinal times-to-first-event in τ $$ tau $$ length follow-up windows that potentially overlap. Multiple imputation (MI) and expectation-solution (ES) approaches appropriate for censored data are developed as part of the model fitting process. A suite of useful analysis outputs are provided from the τ $$ tau $$ -IBR model that include parameter estimates to help interpret the (a) and (b) mixture of event times in the data, estimates of mean τ $$ tau $$ -restricted event-free duration in a τ $$ tau $$ -length follow-up window based on a patient’s covariate profile, and heat maps of raw τ $$ tau $$ -restricted event-free durations observed in the data with censored observations augmented via averages across MI datasets. Simulations indicate good statistical performance of the proposed τ $$ tau $$ -IBR approach to modeling censored recurrent event data. An example is given based on the Azithromycin for Prevention of COPD Exacerbations Trial.

PMID:38386367 | DOI:10.1002/sim.9999

Biometrics. 2024 Jan 29;80(1):ujad035. doi: 10.1093/biomtc/ujad035.

ABSTRACT

In clinical studies of chronic diseases, the effectiveness of an intervention is often assessed using “high cost” outcomes that require long-term patient follow-up and/or are invasive to obtain. While much progress has been made in the development of statistical methods to identify surrogate markers, that is, measurements that could replace such costly outcomes, they are generally not applicable to studies with a small sample size. These methods either rely on nonparametric smoothing which requires a relatively large sample size or rely on strict model assumptions that are unlikely to hold in practice and empirically difficult to verify with a small sample size. In this paper, we develop a novel rank-based nonparametric approach to evaluate a surrogate marker in a small sample size setting. The method developed in this paper is motivated by a small study of children with nonalcoholic fatty liver disease (NAFLD), a diagnosis for a range of liver conditions in individuals without significant history of alcohol intake. Specifically, we examine whether change in alanine aminotransferase (ALT; measured in blood) is a surrogate marker for change in NAFLD activity score (obtained by biopsy) in a trial, which compared Vitamin E ($n=50$) versus placebo ($n=46$) among children with NAFLD.

PMID:38386359 | DOI:10.1093/biomtc/ujad035