Gender and Sport.

Sport faces many challenges in creating fair, interesting, and meaningful competitions that highlight and reward the qualities widely valued in sport, such as natural talents, dedication, and competitive savvy. The Paralympic Games illuminate both the challenge and a thoughtful way of responding by organizing events that group athletes with comparable levels of impairment so that raw physical discrepancies don't overwhelm differences in talent or dedication. It may be helpful to reflect on how gender is used in decisions about who competes against whom. Gender has long served as a rough proxy for differences in size and strength. For sports where size and strength matter, those are the dimensions along which competitors should be matched, not their gender identity. In that sense, gender is incidental to fair competition in sport. Because playing sports is good for people in so many ways, we should provide abundant opportunities that are widely available and enjoyable for all people.

Proximity-driven site-specific cyclization of phage-displayed peptides.

Cyclization provides a general strategy for improving the proteolytic stability, cell membrane permeability and target binding affinity of peptides. Insertion of a stable, non-reducible linker into a disulphide bond is a commonly used approach for cyclizing phage-displayed peptides. However, among the vast collection of cysteine reactive linkers available, few provide the selectivity required to target specific cysteine residues within the peptide in the phage display system, whilst sparing those on the phage capsid. Here, we report the development of a cyclopropenone-based proximity-driven chemical linker that can efficiently cyclize synthetic peptides and peptides fused to a phage-coat protein, and cyclize phage-displayed peptides in a site-specific manner, with no disruption to phage infectivity. Our cyclization strategy enables the construction of stable, highly diverse phage display libraries. These libraries can be used for the selection of high-affinity cyclic peptide binders, as exemplified through model selections on streptavidin and the therapeutic target αvß3.

Barriers to Effective Infection Prevention in the Neonatal Intensive Care Unit: A Qualitative Study.

BACKGROUND: Infection prevention (IP) behaviors such as hand hygiene (HH) and mobile device disinfection are important to reduce the risk of infection transmission from both family members and hospital staff to critically ill neonates. PURPOSE: To inform the design of educational interventions to improve both patient family and staff IP behaviors, we engaged separate groups of nurses and family members to understand perceptions about the spread of infection and barriers to implementing effective IP strategies. METHODS: This was a qualitative study using focus groups to gather data from neonatal nurses and patient family members. Data were triangulated with hospital-wide survey data and analyzed using inductive content analysis. RESULTS: Twelve nurses and 4 patient family members participated. Themes related to communication about IP between staff and family members emerged: stakeholders expressed discomfort with the timing and nature of just-in-time HH education. These communication challenges contributed to stress levels within the neonatal intensive care unit. This finding was reflected in the hospital-wide survey. IMPLICATIONS FOR PRACTICE AND RESEARCH: Steps should be taken to improve communication about IP behaviors between patient family members and frontline staff. Reducing nurse burden of providing just-in-time HH reminders to patient family members through increased IP education may decrease stress and facilitate IP behaviors. This has the potential to decrease infection spread and improve patient outcomes. The development of interventions targeting stakeholder communication is therefore warranted, but additional research is needed to understand the timing and process for delivery of the educational material.

A Survey of Cystic Fibrosis Center Recommendations for Nebulizer Cleaning and Disinfection.

BACKGROUND: Despite advancements in cystic fibrosis (CF) therapeutics, the persistence of chronic infections necessitates continued use of nebulized therapies. Though the Cystic Fibrosis Foundation recommends well-defined cleaning and disinfection of nebulizers to mitigate pathogen exposure risks, discrepancies between Cystic Fibrosis Foundation guidelines, manufacturers' instructions, and variability in center recommendations contribute to confusion and non-standardized practices. METHODS: A digital survey was distributed to directors, associate directors, and care coordinators of CF centers across the United States to investigate the methods, frequency, and educational practices surrounding nebulizer care they provide patients. Responses were analyzed using descriptive techniques and chi-square analyses. RESULTS: Of 855 distributed surveys, 129 respondents provided insights into nebulizer care recommendations. Discrepancies in disinfection frequency were notable, with 18% of respondents recommending disinfecting nebulizers less than daily. Approximately 20% of respondents were unsure if their recommendations aligned with Cystic Fibrosis Foundation guidelines while 73% reported that their recommendations strictly adhered to the published guidelines. Of this 73%, all recommended at least daily cleaning, with 69% specifying cleaning before reuse; and 88% recommended disinfection at least daily, with 36% specifying disinfection before reuse. Only 10% recommended both cleaning and disinfection after every use. Disinfection less than daily was recommended by 11% of the respondents who felt they were strictly following the guidelines. We also highlight respondents who cited barriers to strict adhesion to the published guidelines. CONCLUSIONS: The highlighted variations in CF centers' recommendations for nebulizer care with deviations from Cystic Fibrosis Foundation guidelines underscore the necessity for developing clear and practical guidelines that consider both efficacy and the realities of patient adherence. Collaboration among CF care centers, patients, guideline committees, and other stakeholders is essential to develop recommendations that effectively address the challenges faced by the CF community, ensuring the safe and effective nebulizer use.

A Comparison of Recruitment Methods for a Remote, Nationwide Clinical Trial for COVID-19 Treatment.

This study describes decentralized recruitment and enrollment for a COVID-19 treatment trial, while comparing 5 primary recruitment methods: search engine ads, paid advertising within a national testing company, paid advertising within a regional testing company, electronic health record messages, and word of mouth. These are compared across patient demographics, efficiency, and cost. Clinical Trials Registration: NCT04510194.

A Multicenter Training and Interrater Reliability Study of the BASED Score for Infantile Epileptic Spasms Syndrome.

PURPOSE: The best possible outcomes in infantile epileptic spasms syndrome require electroclinical remission; however, determining electrographic remission is not straightforward. Although the determination of hypsarrhythmia has inadequate interrater reliability (IRR), the Burden of AmplitudeS and Epileptiform Discharges (BASED) score has shown promise for the reliable interictal assessment of infantile epileptic spasms syndrome. Our aim was to develop a BASED training program and assess the IRR among learners. We hypothesized moderate or better IRR for the final BASED score and the presence or absence of epileptic encephalopathy (+/-EE). METHODS: Using a web-based application, 31 learners assessed 12 unmarked EEGs (length 1-6 hours) from children with infantile epileptic spasms syndrome. RESULTS: For all readers, the IRR was good for the final BASED score (intraclass correlation coefficient 0.86) and +/-EE (Marginal Multirater Kappa 0.63). For all readers, the IRR was fair to good for all individual BASED score elements. CONCLUSIONS: These findings support the use of our training program to quickly learn the BASED scoring method. The BASED score may be a valuable clinical and research tool. Given that the IRR for the determination of epileptic encephalopathy is not perfect, clinical acumen remains paramount. Additional experience with the BASED scoring technique among learners and advances in collaborative EEG evaluation platforms may improve IRR.

A Bicyclic Analog of the Linear Peptide Arodyn Is a Potent and Selective Kappa Opioid Receptor Antagonist.

Kappa opioid receptor (KOR) antagonists have potential therapeutic applications in the treatment of stress-induced relapse to substance abuse and mood disorders. The dynorphin A analog arodyn (Ac[Phe1,2,3,Arg4,D-Ala8]dynorphin A-(1-11)-NH2) exhibits potent and selective kappa opioid receptor antagonism. Multiple cyclizations in longer peptides, such as dynorphin and its analogs, can extend the conformational constraint to additional regions of the peptide beyond what is typically constrained by a single cyclization. Here, we report the design, synthesis, and pharmacological evaluation of a bicyclic arodyn analog with two constraints in the opioid peptide sequence. The peptide, designed based on structure-activity relationships of monocyclic arodyn analogs, was synthesized by solid-phase peptide synthesis and cyclized by sequential ring-closing metathesis (RCM) in the C- and N-terminal sequences. Molecular modeling studies suggest similar interactions of key aromatic and basic residues in the bicyclic peptide with KOR as found in the cryoEM structure of KOR-bound dynorphin, despite substantial differences in the backbone conformations of the two peptides. The bicyclic peptide's affinities at KOR and mu opioid receptors (MOR) were determined in radioligand binding assays, and its KOR antagonism was determined in the [35S]GTPγS assay in KOR-expressing cells. The bicyclic analog retains KOR affinity and selectivity (Ki = 26 nM, 97-fold selectivity over MOR) similar to arodyn and exhibits potent KOR antagonism in the dynorphin-stimulated [35S]GTPγS assay. This bicyclic peptide represents a promising advance in preparing cyclic opioid peptide ligands and opens avenues for the rational design of additional bicyclic opioid peptide analogs.

Younger Age and Female Gender Are Associated With Delayed Antibiotics in Pediatric Sepsis.

Sepsis is a leading cause of pediatric mortality and timely antibiotic administration has been shown to improve outcomes. In this retrospective review of a single center sepsis dataset, we identified younger age and female sex as more likely to have delays in antibiotics.

Early trajectories of virological and immunological biomarkers and clinical outcomes in patients admitted to hospital for COVID-19: an international, prospective cohort study.

BACKGROUND: Serial measurement of virological and immunological biomarkers in patients admitted to hospital with COVID-19 can give valuable insight into the pathogenic roles of viral replication and immune dysregulation. We aimed to characterise biomarker trajectories and their associations with clinical outcomes. METHODS: In this international, prospective cohort study, patients admitted to hospital with COVID-19 and enrolled in the Therapeutics for Inpatients with COVID-19 platform trial within the Accelerating COVID-19 Therapeutic Interventions and Vaccines programme between Aug 5, 2020 and Sept 30, 2021 were included. Participants were included from 108 sites in Denmark, Greece, Poland, Singapore, Spain, Switzerland, Uganda, the UK, and the USA, and randomised to placebo or one of four neutralising monoclonal antibodies: bamlanivimab (Aug 5 to Oct 13, 2020), sotrovimab (Dec 16, 2020, to March 1, 2021), amubarvimab-romlusevimab (Dec 16, 2020, to March 1, 2021), and tixagevimab-cilgavimab (Feb 10 to Sept 30, 2021). This trial included an analysis of 2149 participants with plasma nucleocapsid antigen, anti-nucleocapsid antibody, C-reactive protein (CRP), IL-6, and D-dimer measured at baseline and day 1, day 3, and day 5 of enrolment. Day-90 follow-up status was available for 1790 participants. Biomarker trajectories were evaluated for associations with baseline characteristics, a 7-day pulmonary ordinal outcome, 90-day mortality, and 90-day rate of sustained recovery. FINDINGS: The study included 2149 participants. Participant median age was 57 years (IQR 46-68), 1246 (58·0%) of 2149 participants were male and 903 (42·0%) were female; 1792 (83·4%) had at least one comorbidity, and 1764 (82·1%) were unvaccinated. Mortality to day 90 was 172 (8·0%) of 2149 and 189 (8·8%) participants had sustained recovery. A pattern of less favourable trajectories of low anti-nucleocapsid antibody, high plasma nucleocapsid antigen, and high inflammatory markers over the first 5 days was observed for high-risk baseline clinical characteristics or factors related to SARS-CoV-2 infection. For example, participants with chronic kidney disease demonstrated plasma nucleocapsid antigen 424% higher (95% CI 319-559), CRP 174% higher (150-202), IL-6 173% higher (144-208), D-dimer 149% higher (134-165), and anti-nucleocapsid antibody 39% lower (60-18) to day 5 than those without chronic kidney disease. Participants in the highest quartile for plasma nucleocapsid antigen, CRP, and IL-6 at baseline and day 5 had worse clinical outcomes, including 90-day all-cause mortality (plasma nucleocapsid antigen hazard ratio (HR) 4·50 (95% CI 3·29-6·15), CRP HR 3·37 (2·30-4·94), and IL-6 HR 5·67 (4·12-7·80). This risk persisted for plasma nucleocapsid antigen and CRP after adjustment for baseline biomarker values and other baseline factors. INTERPRETATION: Patients admitted to hospital with less favourable 5-day biomarker trajectories had worse prognosis, suggesting that persistent viral burden might drive inflammation in the pathogenesis of COVID-19, identifying patients that might benefit from escalation of antiviral or anti-inflammatory treatment. FUNDING: US National Institutes of Health.

Favorable Antiviral Effect of Metformin on SARS-CoV-2 Viral Load in a Randomized, Placebo-Controlled Clinical Trial of COVID-19.

BACKGROUND: Metformin has antiviral activity against RNA viruses including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The mechanism appears to be suppression of protein translation via targeting the host mechanistic target of rapamycin pathway. In the COVID-OUT randomized trial for outpatient coronavirus disease 2019 (COVID-19), metformin reduced the odds of hospitalizations/death through 28 days by 58%, of emergency department visits/hospitalizations/death through 14 days by 42%, and of long COVID through 10 months by 42%. METHODS: COVID-OUT was a 2 × 3 randomized, placebo-controlled, double-blind trial that assessed metformin, fluvoxamine, and ivermectin; 999 participants self-collected anterior nasal swabs on day 1 (n = 945), day 5 (n = 871), and day 10 (n = 775). Viral load was quantified using reverse-transcription quantitative polymerase chain reaction. RESULTS: The mean SARS-CoV-2 viral load was reduced 3.6-fold with metformin relative to placebo (-0.56 log10 copies/mL; 95% confidence interval [CI], -1.05 to -.06; P = .027). Those who received metformin were less likely to have a detectable viral load than placebo at day 5 or day 10 (odds ratio [OR], 0.72; 95% CI, .55 to .94). Viral rebound, defined as a higher viral load at day 10 than day 5, was less frequent with metformin (3.28%) than placebo (5.95%; OR, 0.68; 95% CI, .36 to 1.29). The metformin effect was consistent across subgroups and increased over time. Neither ivermectin nor fluvoxamine showed effect over placebo. CONCLUSIONS: In this randomized, placebo-controlled trial of outpatient treatment of SARS-CoV-2, metformin significantly reduced SARS-CoV-2 viral load, which may explain the clinical benefits in this trial. Metformin is pleiotropic with other actions that are relevant to COVID-19 pathophysiology. CLINICAL TRIALS REGISTRATION: NCT04510194.

Characterizing healthcare personnel attitudes toward receipt of a voluntary bivalent COVID-19 booster vaccine during a COVID-19 outbreak at a behavioral health hospital in Connecticut.

COVID-19 vaccine uptake in healthcare personnel (HCP) is poor. A cross-sectional survey study of behavioral health HCP was performed. Commonly identified reasons for vaccination were protecting others and oneself. Reasons against were a lack of perceived protection, dosing intervals, and side effects. Assessing vaccination attitudes can assist in uptake strategy.

Optimal timing for an accelerated interim futility analysis incorporating real world data.

BACKGROUND: Randomized controlled trials include interim monitoring guidelines to stop early for safety, efficacy, or futility. Futility monitoring facilitates re-allocation of limited resources. However, conventional methods for interim futility monitoring require a trial to accrue nearly half of the outcome data to make a reliable early stopping decision, limiting its benefit. As early stopping for futility will not inflate type-I error, these analyses are an appealing venue for incorporating external data to improve efficiency. METHODS: We propose a Bayesian approach to futility monitoring leveraging real world data using Semi-Supervised MIXture Multi-source Exchangeability Models, which accounts for both measured and unmeasured differences between data sources. We implement futility monitoring using predictive probabilities and investigate the optimal timing with respect to the expected sample size under the null hypothesis. Because we only incorporate external data during the interim futility analysis the proposed design is not limited by type-I error inflation. RESULTS: When the external and trial data are exchangeable, the proposed method provides a roughly 70 person reduction in expected sample size under the null. Under scenarios where exchangeability does not hold, our approach still provides a 10-20 person reduction in expected sample size under the null with about 80% power. CONCLUSIONS: External data borrowing in interim futility monitoring is a promising venue to improve trial efficiency without type-I error inflation. Approaches that are acceptable to regulatory authorities and leverage the complementary strengths of real world and trial data are vital to more efficiently allocate limited resources amongst clinical trials.

Novel Approaches to Multidrug-Resistant Infections in Cystic Fibrosis.

Patients with cystic fibrosis (CF) often develop respiratory tract infections with pathogenic multidrug-resistant organisms (MDROs) such as methicillin-resistant Staphylococcus aureus, and a variety of gram-negative organisms that include Pseudomonas aeruginosa, Burkholderia sp., Stenotrophomonas maltophilia, Achromobacter xylosoxidans, and nontuberculous mycobacteria (NTM). Despite the introduction of new therapies to address underlying cystic fibrosis transmembrane conductance regulator (CFTR) dysfunction, MDRO infections remain a problem and novel antimicrobial interventions are still needed. Therapeutic approaches include improving the efficacy of existing drugs by adjusting the dose based on differences in CF patient pharmacokinetics/pharmacodynamics, the development of inhaled formulations to reduce systemic adverse events, and the use of newer beta-lactam/beta-lactamase combinations. Alternative innovative therapeutic approaches include the use of gallium and bacteriophages to treat MDRO pulmonary infections including those with extreme antibiotic resistance. However, additional clinical trials are required to determine the optimal dosing and efficacy of these different strategies and to identify patients with CF most likely to benefit from these new treatment options.

Genetic algorithms reveal identity independent representation of emotional expressions.

People readily and automatically process facial emotion and identity, and it has been reported that these cues are processed both dependently and independently. However, this question of identity independent encoding of emotions has only been examined using posed, often exaggerated expressions of emotion, that do not account for the substantial individual differences in emotion recognition. In this study, we ask whether people's unique beliefs of how emotions should be reflected in facial expressions depend on the identity of the face. To do this, we employed a genetic algorithm where participants created facial expressions to represent different emotions. Participants generated facial expressions of anger, fear, happiness, and sadness, on two different identities. Facial features were controlled by manipulating a set of weights, allowing us to probe the exact positions of faces in high-dimensional expression space. We found that participants created facial expressions belonging to each identity in a similar space that was unique to the participant, for angry, fearful, and happy expressions, but not sad. However, using a machine learning algorithm that examined the positions of faces in expression space, we also found systematic differences between the two identities' expressions across participants. This suggests that participants' beliefs of how an emotion should be reflected in a facial expression are unique to them and identity independent, although there are also some systematic differences in the facial expressions between two identities that are common across all individuals. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Network meta analysis to predict the efficacy of an approved treatment in a new indication.

Drug repurposing refers to the process of discovering new therapeutic uses for existing medicines. Compared to traditional drug discovery, drug repurposing is attractive for its speed, cost, and reduced risk of failure. However, existing approaches for drug repurposing involve complex, computationally-intensive analytical methods that are not widely used in practice. Instead, repurposing decisions are often based on subjective judgments from limited empirical evidence. In this article, we develop a novel Bayesian network meta-analysis (NMA) framework that can predict the efficacy of an approved treatment in a new indication and thereby identify candidate treatments for repurposing. We obtain predictions using two main steps: first, we use standard NMA modeling to estimate average relative effects from a network comprised of treatments studied in both indications in addition to one treatment studied in only one indication. Then, we model the correlation between relative effects using various strategies that differ in how they model treatments across indications and within the same drug class. We evaluate the predictive performance of each model using a simulation study and find that the model minimizing root mean squared error of the posterior median for the candidate treatment depends on the amount of available data, the level of correlation between indications, and whether treatment effects differ, on average, by drug class. We conclude by discussing an illustrative example in psoriasis and psoriatic arthritis and find that the candidate treatment has a high probability of success in a future trial.

Effect of Neutralizing Monoclonal Antibody Treatment on Early Trajectories of Virologic and Immunologic Biomarkers in Patients Hospitalized With COVID-19.

BACKGROUND: Neutralizing monoclonal antibodies (nmAbs) failed to show clear benefit for hospitalized patients with coronavirus disease 2019 (COVID-19). Dynamics of virologic and immunologic biomarkers remain poorly understood. METHODS: Participants enrolled in the Therapeutics for Inpatients with COVID-19 trials were randomized to nmAb versus placebo. Longitudinal differences between treatment and placebo groups in levels of plasma nucleocapsid antigen (N-Ag), anti-nucleocapsid antibody, C-reactive protein, interleukin-6, and D-dimer at enrollment, day 1, 3, and 5 were estimated using linear mixed models. A 7-point pulmonary ordinal scale assessed at day 5 was compared using proportional odds models. RESULTS: Analysis included 2149 participants enrolled between August 2020 and September 2021. Treatment resulted in 20% lower levels of plasma N-Ag compared with placebo (95% confidence interval, 12%-27%; P < .001), and a steeper rate of decline through the first 5 days (P < .001). The treatment difference did not vary between subgroups, and no difference was observed in trajectories of other biomarkers or the day 5 pulmonary ordinal scale. CONCLUSIONS: Our study suggests that nmAb has an antiviral effect assessed by plasma N-Ag among hospitalized patients with COVID-19, with no blunting of the endogenous anti-nucleocapsid antibody response. No effect on systemic inflammation or day 5 clinical status was observed. CLINICAL TRIALS REGISTRATION: NCT04501978.

Strategies used for the COVID-OUT decentralized trial of outpatient treatment of SARS-CoV-2.

The COVID-19 pandemic accelerated the development of decentralized clinical trials (DCT). DCT's are an important and pragmatic method for assessing health outcomes yet comprise only a minority of clinical trials, and few published methodologies exist. In this report, we detail the operational components of COVID-OUT, a decentralized, multicenter, quadruple-blinded, randomized trial that rapidly delivered study drugs nation-wide. The trial examined three medications (metformin, ivermectin, and fluvoxamine) as outpatient treatment of SARS-CoV-2 for their effectiveness in preventing severe or long COVID-19. Decentralized strategies included HIPAA-compliant electronic screening and consenting, prepacking investigational product to accelerate delivery after randomization, and remotely confirming participant-reported outcomes. Of the 1417 individuals with the intention-to-treat sample, the remote nature of the study caused an additional 94 participants to not take any doses of study drug. Therefore, 1323 participants were in the modified intention-to-treat sample, which was the a priori primary study sample. Only 1.4% of participants were lost to follow-up. Decentralized strategies facilitated the successful completion of the COVID-OUT trial without any in-person contact by expediting intervention delivery, expanding trial access geographically, limiting contagion exposure, and making it easy for participants to complete follow-up visits. Remotely completed consent and follow-up facilitated enrollment.

Modified interactive Q-learning for attenuating the impact of model misspecification with treatment effect heterogeneity.

A sequential multiple assignment randomized trial, which incorporates multiple stages of randomization, is a popular approach for collecting data to inform personalized and adaptive treatments. There is an extensive literature on statistical methods to analyze data collected in sequential multiple assignment randomized trials and estimate the optimal dynamic treatment regime. Q-learning with linear regression is widely used for this purpose due to its ease of implementation. However, model misspecification is a common problem with this approach, and little attention has been given to the impact of model misspecification when treatment effects are heterogeneous across subjects. This article describes the integrative impact of two possible types of model misspecification related to treatment effect heterogeneity: omitted early-stage treatment effects in late-stage main effect model, and violated linearity assumption between pseudo-outcomes and predictors despite non-linearity arising from the optimization operation. The proposed method, aiming to deal with both types of misspecification concomitantly, builds interactive models into modified parametric Q-learning with Murphy's regret function. Simulations show that the proposed method is robust to both sources of model misspecification. The proposed method is applied to a two-stage sequential multiple assignment randomized trial with embedded tailoring aimed at reducing binge drinking in first-year college students.