Publications

Proteome analysis is increasingly being used in investigations elucidating the molecular basis of disease, identifying diagnostic and prognostic markers, and ultimately improving patient care. We appraised the current status of proteomic investigations using human samples, including the state of the art in proteomic technologies, from sample preparation to data evaluation approaches, as well as key epidemiologic, statistical, and translational issues. We systematically reviewed the most highly cited clinical proteomic studies published between January 2009 and March 2014 that included a minimum of 100 samples, as well as strategies that have been successfully implemented to enhance the translational relevance of proteomic investigations. Limited comparability between studies and lack of specification of biomarker context of use are frequently observed. Nevertheless, there are initial examples of successful biomarker discovery in cross-sectional studies followed by validation in high-risk longitudinal cohorts. Translational potential is currently hindered, as limitations in proteomic investigations are not accounted for. Interdisciplinary communication between proteomics experts, basic researchers, epidemiologists, and clinicians, an orchestrated assimilation of required resources, and a more systematic translational outlook for accumulation of evidence may augment the public health impact of proteomic investigations.

ABSTRACT Background Most countries initially deployed COVID-19 vaccines preferentially in elderly populations. Population-level vaccine effectiveness may be heralded by an increase in the proportion of deaths among non-elderly populations that were less covered by vaccination programs. Methods We collected data from 40 countries on age-stratified COVID-19 deaths during the vaccination period (1/14/2021-5/31/2021) and two control periods (entire pre-vaccination period and excluding the first wave). We meta-analyzed the proportion of deaths in different age groups in vaccination versus control periods in countries with low vaccination rates; (2) countries with age-independent vaccination policies; and (3) countries with standard age-dependent vaccination policies. Findings Countries that prioritized vaccination among older people saw an increasing share of deaths among 0-69 year old people in the vaccination versus the two control periods (summary prevalence ratio 1·32 [95 CI% 1·24-1·41] and 1·35 [95 CI% 1·26-1·44)]. No such change was seen on average in countries with age-independent vaccination policies (1·05 [95 CI% 0·78-1·41 and 0·97 [95 CI% 0·95-1·00], respectively) and limited vaccination (0·93 [95 CI% 0·85-1·01] and 0·95 [95 CI% 0·87-1·03], respectively). Prevalence ratios were associated with the difference of vaccination rates in elderly versus non-elderly people. No significant changes occurred in the share of deaths in age 0-49 among all 0-69 deaths in the vaccination versus pre-vaccination periods. Interpretation The substantial shift in the age distribution of COVID-19 deaths in countries that rapidly implemented vaccination predominantly among elderly may herald the population level-effectiveness of COVID-19 vaccination and a favorable evolution of the pandemic towards endemicity with fewer elderly deaths. Funding This study received no specific funding.

Several studies have investigated whether heterozygosity for a 32-basepair deletion in the CC chemokine receptor 5 gene (CCR5-Delta32 ) affects susceptibility to perinatal HIV-1 infection, but results have been inconclusive. We performed a meta-analysis of published data from 11 studies of HIV-1 perinatally exposed children who were genotyped for the CCR5-Delta32 polymorphism. The crude overall HIV-1 infection rates, by simple data pooling, were 20% (one of five) amongCCR5-Delta32 homozygote children, 39% (131 of 335) among CCR5-Delta32 heterozygote children, and 40% (1408 of 3526) among wild-type CCR5 homozygote children. Compared with wild-type homozygotes, the random effects risk ratio for heterozygotes was 1.04 (95% confidence interval [CI], 0.92-1.17) among all children (N = 3861) and 1.03 (95% CI, 0.90-1.17) among those of European descent (n = 2890). Results were similar when adjusted for the available data on the CCR2-641 polymorphism (n = 1542). The meta-analysis clarifies that perinatal infection is not significantly altered by heterozygosity for CCR5-Delta32 in the child.

This estimation of nationwide CFR and IFR across the entirety of the SARS-CoV-2 pandemic gives crucial insights into the period-dependent variability of the severity of diagnosed COVID-19 cases and its risk factors. Our findings further underline the disproportionate severity of COVID-19 among the elderly and especially nursing home residents.

ABSTRACT Background Artificial intelligence (AI) has emerged as a promising tool in healthcare, with numerous studies indicating its potential to perform as well or better than clinicians. However, a considerable portion of these AI models have only been tested retrospectively, raising concerns about their true effectiveness and potential risks in real-world clinical settings. Methods We conducted a systematic search for randomized controlled trials (RCTs) involving AI algorithms used in various clinical practice fields and locations, published between January 1, 2018, and August 18, 2023. Our study included 84 trials and focused specifically on evaluating intervention characteristics, study endpoints, and trial outcomes, including the potential of AI to improve care management, patient behavior and symptoms, and clinical decision-making. Results Our analysis revealed that 82·1% (69/84) of trials reported positive results for their primary endpoint, highlighting AI’s potential to enhance various aspects of healthcare. Trials predominantly evaluated deep learning systems for medical imaging and were conducted in single-center settings. The US and China had the most trials, with gastroenterology being the most common field of study. However, we also identified areas requiring further research, such as multi-center trials and diverse outcome measures, to better understand AI’s true impact and limitations in healthcare. Conclusion The existing landscape of RCTs on AI in clinical practice demonstrates an expanding interest in applying AI across a range of fields and locations. While most trials report positive outcomes, more comprehensive research, including multi-center trials and diverse outcome measures, is essential to fully understand AI’s impact and limitations in healthcare.

What is wrong with the peer review system? Is peer review sustainable? Useful? What other models exist? These are central yet contentious questions in today’s academic discourse. This perspective critically discusses alternative models and revisions to the peer review system. The authors highlight possible changes to the peer review system, with the goal of fostering further dialog among the main stakeholders, including producers and consumers of scientific research. Neither our list of identified issues with the peer review system nor our discussed resolutions are complete. A point of agreement is that fair assessment and efficient change would require more comprehensive and rigorous data on the various aspects of the peer review system.