Challenges and recommendations for the translation of biomarkers of aging.

Biomarkers of aging (BOA) are quantitative parameters that predict biological age and ideally its changes in response to interventions. In recent years, many promising molecular and omic BOA have emerged with an enormous potential for translational geroscience and improving healthspan. However, clinical translation remains limited, in part due to the gap between preclinical research and the application of BOA in clinical research and other translational settings. We surveyed experts in these areas to better understand current challenges for the translation of aging biomarkers. We identified six key barriers to clinical translation and developed guidance for the field to overcome them. Core recommendations include linking BOA to clinically actionable insights, improving affordability and availability to broad populations and validation of biomarkers that are robust and responsive at the level of individuals. Our work provides key insights and practical recommendations to overcome barriers impeding clinical translation of BOA.

Systematic multi-trait AAV capsid engineering for efficient gene delivery.

Broadening gene therapy applications requires manufacturable vectors that efficiently transduce target cells in humans and preclinical models. Conventional selections of adeno-associated virus (AAV) capsid libraries are inefficient at searching the vast sequence space for the small fraction of vectors possessing multiple traits essential for clinical translation. Here, we present Fit4Function, a generalizable machine learning (ML) approach for systematically engineering multi-trait AAV capsids. By leveraging a capsid library that uniformly samples the manufacturable sequence space, reproducible screening data are generated to train accurate sequence-to-function models. Combining six models, we designed a multi-trait (liver-targeted, manufacturable) capsid library and validated 88% of library variants on all six predetermined criteria. Furthermore, the models, trained only on mouse in vivo and human in vitro Fit4Function data, accurately predicted AAV capsid variant biodistribution in macaque. Top candidates exhibited production yields comparable to AAV9, efficient murine liver transduction, up to 1000-fold greater human hepatocyte transduction, and increased enrichment relative to AAV9 in a screen for liver transduction in macaques. The Fit4Function strategy ultimately makes it possible to predict cross-species traits of peptide-modified AAV capsids and is a critical step toward assembling an ML atlas that predicts AAV capsid performance across dozens of traits.

Challenges and Opportunities in Developing an Oncology Clinical Trial Network in the United States Veterans Affairs Health Care System: The VA STARPORT Experience.

The United States Veterans Affairs (VA) Health Care System has a strong history of conducting impactful oncology randomized clinical trials (RCTs). We developed a phase II/III RCT to test the use of metastasis-directed therapy in Veterans with oligometastatic prostate cancer (OMPC)-the first VA RCT in OMPC that leverages novel imaging and advanced radiotherapy techniques. To accomplish this, we developed a clinical trial network to conduct the study. In this manuscript, we describe several challenges we encountered in study development/conduct and our strategies to address them, with the goal of helping investigators establish robust study networks to conduct clinical trials. In the study start-up, we encountered challenges in timely site activation, and leveraged project management to maximize efficiency. Additionally, there were several changes in the clinical paradigms in imaging and treatment that led to protocol amendments to ensure maximum equipoise, recruitment, and impact of the study. Specifically, we amended the trial to add de novo OMPC patients (from initially only recurrent OMPC) and expanded the study to allow up to 10 metastases (from initially five). Finally, in order to maintain local study team engagement, we developed initiatives to maximize collaboration and add value to the overall clinical program through study participation.

The relationship between workplace justice and self-evaluated nonfatal occupational accidents among healthcare employees in Taiwan: An observational study.

The relationship between workplace justice and nonfatal occupational accidents in a single-payer healthcare system has rarely been explored. As countries strive to achieve and sustain universal health coverage, healthcare workers' occupational safety and health require greater concerns. We used the data from a national survey conducted on randomly sampled Taiwanese workers. One hundred forty eight males and 567 females, with a total of 715 healthcare workers aged 20 to 65, were analyzed. The workplace scale consisted of 4 subcomponents, including distributive justice, interpersonal justice, information justice, and procedural justice, and was dichotomized into low and high groups in each dimension. Logistic regression models examined the relationship between workplace justice and self-evaluated occupational accidents among healthcare employees. The prevalence of self-evaluated occupational accidents in healthcare employees was 15.54% and 11.64% for men and women, respectively. After adjusting variables such as sociodemographic variables, physical job demands, shift work status, work contract, and psychological job demands, regression analyses indicated that health employees with lower distributive justice, interpersonal justice, information justice, and procedural justice were significantly associated with self-evaluated occupational accidents both in males and females. Expanding the study to include healthcare systems in different countries could enhance the generalizability of the findings. Offering specific recommendations for policymakers and healthcare administrators to improve workplace justice and reduce occupational accidents.

Porous organic crystals crosslinked by free-radical reactions.

Two hydrogen-bonded crosslinked organic frameworks (HCOFs) were synthesized via free radical reactions utilizing butadiene and isoprene as crosslinkers. These HCOFs exhibit high crystallinity, enabling detailed structural characterization via single-crystal X-ray diffraction analysis. Subsequently, one of the olefin-rich HCOFs was converted to a hydroxylated framework through hydroboration-oxidation while maintaining the high crystallinity.

Reliable detection of stochastic epigenetic mutations and associations with cardiovascular aging.

Stochastic epigenetic mutations (SEMs) have been proposed as novel aging biomarkers to capture heterogeneity in age-related DNA methylation changes. SEMs are defined as outlier methylation patterns at cytosine-guanine dinucleotide sites, categorized as hypermethylated (hyperSEM) or hypomethylated (hypoSEM) relative to a reference. Because SEMs are defined by their outlier status, it is critical to differentiate extreme values due to technical noise or data artifacts from those due to real biology. Using technical replicate data, we found SEM detection is not reliable: across 3 datasets, 24 to 39% of hypoSEM and 46 to 67% of hyperSEM are not shared between replicates. We identified factors influencing SEM reliability-including blood cell type composition, probe beta-value statistics, genomic location, and presence of SNPs. We used these factors in a training dataset to build a machine learning-based filter that removes unreliable SEMs, and found this filter enhances reliability in two independent validation datasets. We assessed associations between SEM loads and aging phenotypes in the Framingham Heart Study and discovered that associations with aging outcomes were in large part driven by hypoSEMs at baseline methylated probes and hyperSEMs at baseline unmethylated probes, which are the same subsets that demonstrate highest technical reliability. These aging associations were preserved after filtering out unreliable SEMs and were enhanced after adjusting for blood cell composition. Finally, we utilized these insights to formulate best practices for SEM detection and introduce a novel R package, SEMdetectR, which uses parallel programming for efficient SEM detection with comprehensive options for detection, filtering, and analysis.

An AAV capsid reprogrammed to bind human transferrin receptor mediates brain-wide gene delivery.

Developing vehicles that efficiently deliver genes throughout the human central nervous system (CNS) will broaden the range of treatable genetic diseases. We engineered an adeno-associated virus (AAV) capsid, BI-hTFR1, that binds human transferrin receptor (TfR1), a protein expressed on the blood-brain barrier. BI-hTFR1 was actively transported across human brain endothelial cells and, relative to AAV9, provided 40 to 50 times greater reporter expression in the CNS of human TFRC knockin mice. The enhanced tropism was CNS-specific and absent in wild-type mice. When used to deliver GBA1, mutations of which cause Gaucher disease and are linked to Parkinson's disease, BI-hTFR1 substantially increased brain and cerebrospinal fluid glucocerebrosidase activity compared with AAV9. These findings establish BI-hTFR1 as a potential vector for human CNS gene therapy.

Age-Invariant Genes: Multi-Tissue Identification and Characterization of Murine Reference Genes.

Studies of the aging transcriptome focus on genes that change with age. But what can we learn from age-invariant genes-those that remain unchanged throughout the aging process? These genes also have a practical application: they serve as reference genes (often called housekeeping genes) in expression studies. Reference genes have mostly been identified and validated in young organisms, and no systematic investigation has been done across the lifespan. Here, we build upon a common pipeline for identifying reference genes in RNA-seq datasets to identify age-invariant genes across seventeen C57BL/6 mouse tissues (brain, lung, bone marrow, muscle, white blood cells, heart, small intestine, kidney, liver, pancreas, skin, brown, gonadal, marrow, and subcutaneous adipose tissue) spanning 1 to 21+ months of age. We identify 9 pan-tissue age-invariant genes and many tissue-specific age-invariant genes. These genes are stable across the lifespan and are validated in independent bulk RNA-seq datasets and RT-qPCR. We find age-invariant genes have shorter transcripts on average and are enriched for CpG islands. Interestingly, pathway enrichment analysis for age-invariant genes identifies an overrepresentation of molecular functions associated with some, but not all, hallmarks of aging. Thus, though hallmarks of aging typically involve changes in cell maintenance mechanisms, select genes associated with these hallmarks resist fluctuations in expression with age. Finally, our analysis concludes no classical reference gene is appropriate for aging studies in all tissues. Instead, we provide tissue-specific and pan-tissue genes for assays utilizing reference gene normalization (i.e., RT-qPCR) that can be applied to animals across the lifespan.

Hyperpolarized [1-13C]-pyruvate MRS evaluates immune potential and predicts response to radiotherapy in cervical cancer.

BACKGROUND: Monitoring pyruvate metabolism in the spleen is important for assessing immune activity and achieving successful radiotherapy for cervical cancer due to the significance of the abscopal effect. We aimed to explore the feasibility of utilizing hyperpolarized (HP) [1-13C]-pyruvate magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) to evaluate pyruvate metabolism in the human spleen, with the aim of identifying potential candidates for radiotherapy in cervical cancer. METHODS: This prospective study recruited six female patients with cervical cancer (median age 55 years; range 39-60) evaluated using HP [1-13C]-pyruvate MRI/MRS at baseline and 2 weeks after radiotherapy. Proton (1H) diffusion-weighted MRI was performed in parallel to estimate splenic cellularity. The primary outcome was defined as tumor response to radiotherapy. The Student t-test was used for comparing 13C data between the groups. RESULTS: The splenic HP [1-13C]-lactate-to-total carbon (tC) ratio was 5.6-fold lower in the responders than in the non-responders at baseline (p = 0.009). The splenic [1-13C]-lactate-to-tC ratio revealed a 1.7-fold increase (p = 0.415) and the splenic [1-13C]-alanine-to-tC ratio revealed a 1.8-fold increase after radiotherapy (p = 0.482). The blood leukocyte differential count revealed an increased proportion of neutrophils two weeks following treatment, indicating enhanced immune activity (p = 0.013). The splenic apparent diffusion coefficient values between the groups were not significantly different. CONCLUSIONS: This exploratory study revealed the feasibility of HP [1-13C]-pyruvate MRS of the spleen for evaluating baseline immune potential, which was associated with clinical outcomes of cervical cancer after radiotherapy. TRIAL REGISTRATION: ClinicalTrials.gov NCT04951921 , registered 7 July 2021. RELEVANCE STATEMENT: This prospective study revealed the feasibility of using HP 13C MRI/MRS for assessing pyruvate metabolism of the spleen to evaluate the patients' immune potential that is associated with radiotherapeutic clinical outcomes in cervical cancer. KEY POINTS: • Effective radiotherapy induces abscopal effect via altering immune metabolism. • Hyperpolarized 13C MRS evaluates patients' immune potential non-invasively. • Pyruvate-to-lactate conversion in the spleen is elevated following radiotherapy.

A traffic-induced shift of ultrafine particle sources under COVID-19 soft lockdown in a subtropical urban area.

During the unprecedented COVID-19 city lockdown, a unique opportunity arose to dissect the intricate dynamics of urban air quality, focusing on ultrafine particles (UFPs) and volatile organic compounds (VOCs). This study delves into the nuanced interplay between traffic patterns and UFP emissions in a subtropical urban setting during the spring-summer transition of 2021. Leveraging meticulous roadside measurements near a traffic nexus, our investigation unravels the intricate relationship between particle number size distribution (PNSD), VOCs mixing ratios, and detailed vehicle activity metrics. The soft lockdown era, marked by a 20-27% dip in overall traffic yet a surprising surge in early morning motorcycle activity, presented a natural experiment. We observed a consequential shift in the urban aerosol regime: the decrease in primary emissions from traffic substantially amplified the role of aged particles and secondary aerosols. This shift was particularly pronounced under stagnant atmospheric conditions, where reduced dilution exacerbated the influence of alternative emission sources, notably solvent evaporation, and was further accentuated with the resumption of normal traffic flows. A distinct seasonal trend emerged as warmer months approached, with aromatic VOCs such as toluene, ethylbenzene, and xylene not only increasing but also significantly contributing to more frequent particle growth events. These findings spotlight the criticality of targeted strategies at traffic hotspots, especially during periods susceptible to weak atmospheric dilution, to curb UFP and precursor emissions effectively. As we stand at the cusp of widespread vehicle electrification, this study underscores the imperative of a holistic approach to urban air quality management, embracing the complexities of primary emission reductions and the resultant shifts in atmospheric chemistry.

Current methods for hyperpolarized [1-13C]pyruvate MRI human studies.

MRI with hyperpolarized (HP) 13C agents, also known as HP 13C MRI, can measure processes such as localized metabolism that is altered in numerous cancers, liver, heart, kidney diseases, and more. It has been translated into human studies during the past 10 years, with recent rapid growth in studies largely based on increasing availability of HP agent preparation methods suitable for use in humans. This paper aims to capture the current successful practices for HP MRI human studies with [1-13C]pyruvate-by far the most commonly used agent, which sits at a key metabolic junction in glycolysis. The paper is divided into four major topic areas: (1) HP 13C-pyruvate preparation; (2) MRI system setup and calibrations; (3) data acquisition and image reconstruction; and (4) data analysis and quantification. In each area, we identified the key components for a successful study, summarized both published studies and current practices, and discuss evidence gaps, strengths, and limitations. This paper is the output of the "HP 13C MRI Consensus Group" as well as the ISMRM Hyperpolarized Media MR and Hyperpolarized Methods and Equipment study groups. It further aims to provide a comprehensive reference for future consensus, building as the field continues to advance human studies with this metabolic imaging modality.

Analysis of environmental factors influencing endemic cholera risks in sub-Saharan Africa.

The recurring cholera outbreaks in sub-Saharan Africa are of growing concern, especially considering the potential acceleration in the global trend of larger and more lethal cholera outbreaks due to the impacts of climate change. However, there is a scarcity of evidence-based research addressing the environmental and infrastructure factors that sustain cholera recurrence in Africa. This study adopts a statistical approach to investigate over two decades of endemic cholera outbreaks and their relationship with five environmental factors: water provision, sanitation provision, raising temperatures, increased rainfall and GDP. The analysis covers thirteen of the forty-two countries in the mainland sub-Saharan region, collectively representing one-third of the region's territory and half of its population. This breadth enables the findings to be generalised at a regional level. Results from all analyses consistently associate water provision with cholera reduction. The stratified model links increased water provision with a reduction in cholera risk that ranged from 4.2 % to 84.1 % among eight countries (out of 13 countries) as well as a reduction of such risk that ranged from 9.8 % to 68.9 % when there is increased sanitation provision, which was observed in nine countries (out of 13). These results indicate that the population's limited access to water and sanitation, as well as the rise in temperatures, are critical infrastructure and environmental factors contributing to endemic cholera and the heightened risk of outbreaks across the sub-Saharan region. Therefore, these are key areas for targeted interventions and cross-border collaboration to enhance resilience to outbreaks and lead to the end of endemic cholera in the region. However, it is important to interpret the results of this study with caution; hence, further investigation is recommended to conduct a more detailed analysis of the impact of infrastructure and environmental factors on reducing cholera risk.

Validation of biomarkers of aging.

The search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve as surrogate endpoints for the evaluation of interventions promoting healthy aging and longevity. However, no consensus exists on how biomarkers of aging should be validated before their translation to the clinic. Here, we review current efforts to evaluate the predictive validity of omic biomarkers of aging in population studies, discuss challenges in comparability and generalizability and provide recommendations to facilitate future validation of biomarkers of aging. Finally, we discuss how systematic validation can accelerate clinical translation of biomarkers of aging and their use in gerotherapeutic clinical trials.

Task Activation Results in Regional 13 C-Lactate Signal Increase in the Human Brain.

Hyperpolarized- 13 C magnetic resonance imaging (HP- 13 C MRI) was used to image changes in 13 C-lactate signal during a visual stimulus condition in comparison to an eyes-closed control condition. Whole-brain 13 C-pyruvate, 13 C-lactate and 13 C-bicarbonate production was imaged in healthy volunteers (N=6, ages 24-33) for the two conditions using two separate hyperpolarized 13 C-pyruvate injections. BOLD-fMRI scans were used to delineate regions of functional activation. 13 C-metabolite signal was normalized by 13 C-metabolite signal from the brainstem and the percentage change in 13 C-metabolite signal conditions was calculated. A one-way Wilcoxon signed-rank test showed a significant increase in 13 C-lactate in regions of activation when compared to the remainder of the brain ( p = 0.02, V = 21). No significant increase was observed in 13 C-pyruvate ( p = 0.11, V = 17) or 13 C-bicarbonate ( p = 0.95, V = 3) signal. The results show an increase in 13 C-lactate production in the activated region that is measurable with HP- 13 C MRI.

Evidence of 13 C-lactate oxidation in the human brain from hyperpolarized 13 C-MRI.

PURPOSE: To test the hypothesis that lactate oxidation contributes to the 13 $$ {}^{13} $$ C-bicarbonate signal observed in the awake human brain using hyperpolarized 13 $$ {}^{13} $$ C MRI. METHODS: Healthy human volunteers (N = 6) were scanned twice using hyperpolarized 13 $$ {}^{13} $$ C-MRI, with increased radiofrequency saturation of 13 $$ {}^{13} $$ C-lactate on one set of scans. 13 $$ {}^{13} $$ C-lactate, 13 $$ {}^{13} $$ C-bicarbonate, and 13 $$ {}^{13} $$ C-pyruvate signals for 132 brain regions across each set of scans were compared using a clustered Wilcoxon signed-rank test. RESULTS: Increased 13 $$ {}^{13} $$ C-lactate radiofrequency saturation resulted in a significantly lower 13 $$ {}^{13} $$ C-bicarbonate signal (p = 0.04). These changes were observed across the majority of brain regions. CONCLUSION: Radiofrequency saturation of 13 $$ {}^{13} $$ C-lactate leads to a decrease in 13 $$ {}^{13} $$ C-bicarbonate signal, demonstrating that the 13 $$ {}^{13} $$ C-lactate generated from the injected 13 $$ {}^{13} $$ C-pyruvate is being converted back to 13 $$ {}^{13} $$ C-pyruvate and oxidized throughout the human brain.

Beyond flood hazard. Mapping the loss probability of pedestrians to improve risk estimation and communication.

The effective communication of flood hazard and risk is a necessary step to foster preparedness and resilience, hence reducing the detrimental impacts of flooding events. Classical flood maps, which show flow depth and velocity, have often proved to be incomprehensible to the majority of people. Some recent studies used color maps to convey the spatial distribution of diverse hazard indexes that, accounting for both water depth and velocity, are intended to communicate the hazard degree in a more intelligible way. It is first shown that these hazard indexes have some inherent limitations, as for example the implicit assumption of a linear relationship between flood hazard and flow velocity. As an alternative, we propose to map the loss probability (LP) of pedestrians exposed to floodwaters, which is a physics-based and data-consistent risk index accounting for both hazard and vulnerability. LP can be easily computed and allows for a sounder estimation and a more effective communication of flood risk to the general public.

Geroscience-Centric Perspective for Geriatric Psychiatry: Integrating Aging Biology With Geriatric Mental Health Research.

The geroscience hypothesis asserts that physiological aging is caused by a small number of biological pathways. Despite the explosion of geroscience research over the past couple of decades, the research on how serious mental illnesses (SMI) affects the biological aging processes is still in its infancy. In this review, we aim to provide a critical appraisal of the emerging literature focusing on how we measure biological aging systematically, and in the brain and how SMIs affect biological aging measures in older adults. We will also review recent developments in the field of cellular senescence and potential targets for interventions for SMIs in older adults, based on the geroscience hypothesis.

Cytokine enrichment in deep cerebellar nuclei is contributed by multiple glial populations and linked to reduced amyloid plaque pathology.

Alzheimer's disease (AD) pathology and amyloid-beta (Aß) plaque deposition progress slowly in the cerebellum compared to other brain regions, while the entorhinal cortex (EC) is one of the most vulnerable regions. Using a knock-in AD mouse model (App KI), we show that within the cerebellum, the deep cerebellar nuclei (DCN) has particularly low accumulation of Aß plaques. To identify factors that might underlie differences in the progression of AD-associated neuropathology across regions, we profiled gene expression in single nuclei (snRNAseq) across all cell types in the DCN and EC of wild-type (WT) and App KI male mice at age 7 months. We found differences in expression of genes associated with inflammatory activation, PI3K-AKT signalling, and neuron support functions between both regions and genotypes. In WT mice, the expression of interferon-response genes in microglia is higher in the DCN than the EC and this enrichment is confirmed by RNA in situ hybridisation, and measurement of inflammatory cytokines by protein array. Our analyses also revealed that multiple glial populations are responsible for establishing this cytokine-enriched niche. Furthermore, homogenates derived from the DCN induced inflammatory gene expression in BV2 microglia. We also assessed the relationship between the DCN microenvironment and Aß pathology by depleting microglia using a CSF1R inhibitor PLX5622 and saw that, surprisingly, the expression of a subset of inflammatory cytokines was increased while plaque abundance in the DCN was further reduced. Overall, our study revealed the presence of a cytokine-enriched microenvironment unique to the DCN that when modulated, can alter plaque deposition.

Enhancing urban flood forecasting in drainage systems using dynamic ensemble-based data mining.

This study presents a novel approach for urban flood forecasting in drainage systems using a dynamic ensemble-based data mining model which has yet to be utilised properly in this context. The proposed method incorporates an event identification technique and rainfall feature extraction to develop weak learner data mining models. These models are then stacked to create a time-series ensemble model using a decision tree algorithm and confusion matrix-based blending method. The proposed model was compared to other commonly used ensemble models in a real-world urban drainage system in the UK. The results show that the proposed model achieves a higher hit rate compared to other benchmark models, with a hit rate of around 85% vs 70 % for the next 3 h of forecasting. Additionally, the proposed smart model can accurately classify various timesteps of flood or non-flood events without significant lag times, resulting in fewer false alarms, reduced unnecessary risk management actions, and lower costs in real-time early warning applications. The findings also demonstrate that two features, "antecedent precipitation history" and "seasonal time occurrence of rainfall," significantly enhance the accuracy of flood forecasting with a hit rate accuracy ranging from 60 % to 10 % for a lead time of 15 min to 3 h.