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Micro-ultrasound has recently been introduced as a low-cost alternative to multi-parametric MRI for imaging prostate cancer. Early clinical studies have demonstrated promising results; however, robust validation via comparison with whole-mount pathology has yet to be achieved. Due to micro-ultrasound probe design and tissue deformation during scanning, it is difficult to accurately correlate micro-ultrasound imaging planes with ground truth whole-mount pathology slides. In this study, we developed a multi-step methodology to co-register micro-ultrasound and MRI to whole-mount pathology. The three-step process had a registration error of 3.90 ± 0.11 mm and consists of: (1) micro-ultrasound image reconstruction, (2) 3D landmark registration of micro-ultrasound to MRI, and (3) 2D capsule registration of MRI to whole-mount pathology. This process was then used in a preliminary reader study to compare the diagnostic accuracy of micro-ultrasound and MRI in 15 patients who underwent radical prostatectomy for prostate cancer. Micro-ultrasound was found to have equivalent performance to retrospective MRI review for index lesion detection (91.7% vs. 80%), while demonstrating an increased detection of tumor extent (52.5% vs. 36.7%) with similar false positive regions-of-interest (38.3% vs. 40.8%). Prospective MRI review had reduced detection of index lesions (73.3%) and tumor extent (18.9%) but improved false positive regions-of-interest (22.7%) relative to micro-ultrasound and retrospective MRI. Further evaluation is needed with a larger sample size.

Radiopharmaceutical therapy using α -emitting 225 Ac is an emerging treatment for patients with advanced metastatic cancers. Measurement of the spatial dose distribution in organs and tumors is needed to inform treatment dose prescription and reduce off-target toxicity, at not only organ but also sub-organ scales. Digital autoradiography with α -sensitive detection devices can measure radioactivity distributions at 20-40 μm resolution, but anatomical characterization is typically limited to 2D. We collected digital autoradiographs across whole tissues to generate 3D dose volumes and used them to evaluate the simultaneous tumor control and regional kidney dosimetry of a novel therapeutic radiopharmaceutical for prostate cancer, [225Ac]Ac-Macropa-PEG4-YS5, in mice. 22Rv1 xenograft-bearing mice treated with 18.5 kBq of [225Ac]Ac-Macropa-PEG4-YS5 were sacrificed at 24 h and 168 h post-injection for quantitative α -particle digital autoradiography and hematoxylin and eosin staining. Gamma-ray spectroscopy of biodistribution data was used to determine temporal dynamics and 213 Bi redistribution. Tumor control probability and sub-kidney dosimetry were assessed. Heterogeneous 225 Ac spatial distribution was observed in both tumors and kidneys. Tumor control was maintained despite heterogeneity if cold spots coincided with necrotic regions. 225 Ac dose-rate was highest in the cortex and renal vasculature. Extrapolation of tumor control suggested that kidney absorbed dose could be reduced by 41% while maintaining 90% TCP. The 3D dosimetry methods described allow for whole tumor and organ dose measurements following 225 Ac radiopharmaceutical therapy, which correlate to tumor control and toxicity outcomes.

In vitro evolution and whole genome analysis has proven to be a powerful method for studying the mechanism of action of small molecules in many haploid microbes but has generally not been applied to human cell lines in part because their diploid state complicates the identification of variants that confer drug resistance. To determine if haploid human cells could be used in MOA studies, we evolved resistance to five different anticancer drugs (doxorubicin, gemcitabine, etoposide, topotecan, and paclitaxel) using a near-haploid cell line (HAP1) and then analyzed the genomes of the drug resistant clones, developing a bioinformatic pipeline that involved filtering for high frequency alleles predicted to change protein sequence, or alleles which appeared in the same gene for multiple independent selections with the same compound. Applying the filter to sequences from 28 drug resistant clones identified a set of 21 genes which was strongly enriched for known resistance genes or known drug targets (TOP1, TOP2A, DCK, WDR33, SLCO3A1). In addition, some lines carried structural variants that encompassed additional known resistance genes (ABCB1, WWOX and RRM1). Gene expression knockdown and knockout experiments of 10 validation targets showed a high degree of specificity and accuracy in our calls and demonstrates that the same drug resistance mechanisms found in diverse clinical samples can be evolved, discovered and studied in an isogenic background.

Adults with Down syndrome have a genetic form of Alzheimer's disease (AD) and evidence of cerebrovascular disease across the AD continuum, despite few systemic vascular risk factors. The onset and progression of AD in Down syndrome is highly age-dependent, but it is unknown at what age cerebrovascular disease emerges and what factors influence its severity. In the Alzheimer's Biomarker Consortium-Down Syndrome study (ABC-DS; n = 242; age = 25-72), we estimated the age inflection point at which MRI-based white matter hyperintensities (WMH), enlarged perivascular spaces (PVS), microbleeds, and infarcts emerge in relation to demographic data, risk factors, amyloid and tau, and AD diagnosis. Enlarged PVS and infarcts appear to develop in the early 30s, while microbleeds, WMH, amyloid, and tau emerge in the mid to late 30s. Age-residualized WMH were higher in women, in individuals with dementia, and with lower body mass index. Participants with hypertension and APOE-ε4 had higher age-residualized PVS and microbleeds, respectively. Lifespan trajectories demonstrate a dramatic cerebrovascular profile in adults with Down syndrome that appears to evolve developmentally in parallel with AD pathophysiology approximately two decades prior to dementia symptoms.

Chemical pesticide delivery is a fundamental aspect of agriculture. However, the extensive use of pesticides severely endangers the ecosystem because they accumulate on crops, in soil, as well as in drinking and groundwater. New frontiers in nano-engineering have opened the door for precision agriculture. We introduced Tobacco mild green mosaic virus (TMGMV) as a viable delivery platform with a high aspect ratio and favorable soil mobility. In this work, we assess the use of TMGMV as a chemical nanocarrier for agriculturally relevant cargo. While plant viruses are usually portrayed as rigid/solid structures, these are "dynamic materials," and they "breathe" in solution in response to careful adjustment of pH or bathing media [e.g., addition of solvent such as dimethyl sulfoxide (DMSO)]. Through this process, coat proteins (CPs) partially dissociate leading to swelling of the nucleoprotein complexes-allowing for the infusion of active ingredients (AI), such as pesticides [e.g., fluopyram (FLP), clothianidin (CTD), rifampicin (RIF), and ivermectin (IVM)] into the macromolecular structure. We developed a "breathing" method that facilitates inter-coat protein cargo loading, resulting in up to  ~ 1000 AIs per virion. This is of significance since in the agricultural setting, there is a need to develop nanoparticle delivery strategies where the AI is not chemically altered, consequently avoiding the need for regulatory and registration processes of new compounds. This work highlights the potential of TMGMV as a pesticide nanocarrier in precision farming applications; the developed methods likely would be applicable to other protein-based nanoparticle systems.

Traumatic brain injury (TBI) affects how the brain functions in the short and long term. Resulting patient outcomes across physical, cognitive, and psychological domains are complex and often difficult to predict. Major challenges to developing personalized treatment for TBI include distilling large quantities of complex data and increasing the precision with which patient outcome prediction (prognoses) can be rendered. We developed and applied interpretable machine learning methods to TBI patient data. We show that complex data describing TBI patients intake characteristics and outcome phenotypes can be distilled to smaller sets of clinically interpretable latent factors. We demonstrate that 19 clusters of TBI outcomes can be predicted from intake data, a ~ 6× improvement in precision over clinical standards. Finally, we show that 36% of the outcome variance across patients can be predicted. These results demonstrate the importance of interpretable machine learning applied to deeply characterized patients for data-driven distillation and precision prognosis.

Human milk contains over 200 distinct oligosaccharides, which are critical to shaping the developing neonatal gut microbiome. To investigate whether a complex mixture of human milk oligosaccharides (HMOs) would similarly modulate the adult gut microbiome, HMO-Concentrate derived from pooled donor breast milk was administered orally to 32 healthy adults for 7 days followed by 21 days of monitoring. Fecal samples were collected for 16S rRNA gene sequencing, shotgun metagenomics, and metabolomics analyses. HMO-Concentrate induced dose-dependent Bifidobacterium expansion, reduced microbial diversity, and altered microbial gene content. Following HMO cessation, a microbial succession occurred with diverse taxonomic changes-including Bacteroides expansion-that persisted through day 28. This was associated with altered microbial gene content, shifts in serum metabolite levels, and increased circulating TGFβ and IL-10. Incubation of cultured adult microbiota with HMO-Concentrate induced dose-dependent compositional shifts that were not recapitulated by individual HMOs or defined mixtures of the 10 most abundant HMOs in HMO-Concentrate at their measured concentrations. These findings support that pooled donor HMOs can exert direct effects on adult gut microbiota and that complex mixtures including low abundance HMOs present in donor milk may be required for maximum effect.Registration: ClinicalTrials.gov NCT05516225.